Next Article in Journal
Impact of Chinese Heritage, Cultural Protection, and Green Innovation on Tourism Development
Previous Article in Journal
The Impact of Data Element Marketization on Green Total Factor Energy Efficiency: Empirical Evidence from China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Impact of Application Programming Interfaces (APIs) Economy on Digital Economics in Saudi Arabia

by
Mohamed Ali Ali
1,* and
Sara Mohamed Salih
2
1
Department of Finance, College of Business Administration in Hawtat Bani Tamim, Prince Sattam bin Abdulaziz University, Al-Kharj 16273, Saudi Arabia
2
Department of Information Systems, College of Science and Human Studies in Hawtat Bani Tamim, Prince Sattam bin Abdulaziz University, Al-Kharj 16273, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(9), 4104; https://doi.org/10.3390/su17094104
Submission received: 19 March 2025 / Revised: 22 April 2025 / Accepted: 29 April 2025 / Published: 1 May 2025

Abstract

Using a panel Autoregressive Distributed Lag (ARDL) model, this study examines the effects of the adoption of Application Programming Interfaces (APIs) on the digital economy of Saudi Arabia, using monthly data from 2015 to 2024 from the World Development Indicators and Bloomberg. The results show that API Adoption Rate (APIAR) has a positive long-term influence on the Digital Economy Index (DEI), highlighting APIs as a transformative tool that foster innovation, increase scalability within enterprises, and enhance digital transactions in line with SDG 9: Industry, Innovation, and Infrastructure. The findings also indicate that the Number of Active APIs (NAAPIs) exerts a significant and positive effect on DEI in both short- and long-term, which aligns with SDG 8: Decent Work and Economic Growth by fostering accelerated digital transformation and new innovation-driven job opportunities in addition to entrepreneurship via API-driven platforms. API Investment (APII) exhibits a beneficial short-term effect on DEI; nevertheless, it is not significant in the long run, indicating the need for strategic and continuous investment. This finding resonates with SDG 17: Partnerships for the Goals, highlighting the significant role of public–private collaboration in enhancing digital infrastructure and enabling AI solutions. Building on these results, there is an urgent need to improve consistent API ecosystems, enhance collaborative partnerships, and align API strategies to national aspirations for driving Saudi Arabia’s digital economic growth and supporting Vision 2030 and the UN’s SDGs.

1. Introduction

The Application Programming Interface (API) economy has emerged as a key driver of digital transformation, enabling seamless data exchange, automation, and innovation across industries. APIs serve as intermediaries that allow different software applications to communicate, facilitating business integration and enhancing operational efficiency [1,2]. Their role extends beyond traditional IT functions, improving innovation in financial technology (fintech), healthcare, logistics, and government services [3]. As a result, organizations worldwide are increasingly leveraging APIs to enhance customer experience, streamline operations, and create new revenue streams. Globally, the API management market is expected to grow from USD 4.5 billion in 2022 to USD 13.7 billion by 2027 at a compound annual growth rate (CAGR) of 25.1% [4]. This rapid expansion highlights the critical role of APIs in modern digital economies, driving advancements in cloud computing, artificial intelligence, and big data analytics [5,6].
Saudi Arabia’s API economy is driving digital transformation across the finance, healthcare, and education sectors. APIs enable seamless integration, foster innovation, and support open banking, creating a more competitive financial ecosystem [7,8]. They also contribute to sustainable development by enhancing efficiency, reducing costs, and promoting inclusivity, directly aligning with the Sustainable Development Goals. As of 2024, the digital economy represents about 14% of the Kingdom’s GDP. A national survey by GASTAT, in collaboration with OECD and UNCTAD, highlights the growing role of APIs in automating processes, improving service delivery, and accelerating digital growth [9].
Cloud computing further supports this API-driven ecosystem, with 48% of businesses using cloud services. API adoption is highest in the information and communication sector (68.3%), followed by education (66.9%) and professional services (59.5%) [10]. Around 20.3% of businesses offer digital services through API integration, led by education (44.5%) and accommodation (39.9%). In e-procurement, 18.5% of enterprises participate, especially in information and communication (40.1%) [11]. Additionally, 60.1% of institutions use smart technologies like surveillance and smart meters, with the highest uptake in health (67.4%) and finance, insurance, and education (65.2%) [12,13], reflecting a shift toward automation and data-driven decision-making.
Saudi Arabia has recently established itself as a regional leader in digital transformation through Vision 2030, a strategic framework to diversify the Kingdom’s economy and reduce its dependence on oil revenues. Aligned with this vision, Saudi Arabia has invested over USD 15 billion in emerging technologies such as artificial intelligence (AI), blockchain, 5G, and cloud computing, in which APIs are key enablers [14]. The Saudi Ministry of Communications and Information Technology (MCIT) aims to raise the contribution of the ICT sector to GDP from 2.4% to 4.3%, among other goals [15]. Other initiatives, including the National Digital Transformation Program, the Saudi Data and AI Authority (SDAIA), and the Open Banking Framework, are enhancing API adoption to foster business innovation, improve service delivery, and boost cybersecurity [16]. APIs have enabled a new generation of software development called fintech. API-led applications have proliferated in the financial sector, making Saudi Arabia one of the biggest fintech hubs in the MENA region [17].
Despite noting some advantages, the economic benefits of API adoption in Saudi Arabia are still under discussion. APIs play a role in increasing efficiency and economic growth in developed economies [18], but little is known empirically about their impact on digital economic development in emerging markets. Indeed, APIs demand cloud-based apps, digital payment services, embedded finance and e-commerce solutions, positioning them as a key driver of Saudi Arabia’s digital economy growth [19]. Nevertheless, no extensive study has explored how impactful API adoption is on economic parameters such as the digital transformation index, e-commerce growth, and digital GDP contribution.
Additionally, several challenges are preventing many from using APIs, thus reducing their potential to enhance economic growth in Saudi Arabia. However, substantial obstacles to widespread implementation include regulatory constraints, cybersecurity risks, lack of standardization, and limited API monetization strategies [20]. API-driven solutions have been efficiently integrated into large enterprises. Still, small and medium-sized enterprises (SMEs) continue to battle API adoption due to implementation costs and a lack of technical expertise [21]. As digital transformation becomes increasingly critical to economic development, it is crucial to understand how API adoption relates to the performance of digital economies in order to inform policy development, business strategies, and investment decisions [22].
This research aims to address the gap in the existing literature through a holistic empirical study on the effects of API adoption on the health of the digital economy in Saudi Arabia. Using a panel Autoregressive Distributed Lag (ARDL) model, this examination analyzes monthly data from 2015 to 2024, obtained from the World Development Indicators and Bloomberg, to assess the impact of APIs on critical digital economy indicators, namely the digital transformation index, e-commerce growth, and the contribution of digital GDP. Through APIs that allow for instant integration amongst digital platforms, they facilitate business efficiencies, tech innovation, and market growth. This study addresses a novel angle compared to the existing literature regarding the API economy and KSA’s digital economic growth, which has already been explored in great depth, covering various sectors and the digital landscape in general.
This study offers critical insights for various stakeholders. Policymakers can use the findings to develop regulations that promote API-driven digital infrastructure, ensuring data security and interoperability. Businesses can understand how API adoption enhances operational efficiency, customer experience, and market competitiveness. Investors and technology firms can gain data-driven insights into the scalability and profitability of API-based digital business models [23].
A key novelty of this research lies in its focus on the relationship between API adoption and critical digital economy metrics, including the digital transformation index, e-commerce growth, and digital GDP contribution. Unlike prior studies that assess digitalization from a macroeconomic perspective, this research isolates APIs as a core technological enabler of economic efficiency, innovation, and market expansion in Saudi Arabia. The findings will provide empirical evidence on how API integration enhances business agility, facilitates seamless platform connectivity, and accelerates the digital economy’s overall growth.
In addition, the study aligns with the United Nations Sustainable Development Goals (SDGs), particularly the 9th SDG, which focuses on building resilient infrastructure, promoting sustainable industrialization and fostering innovation. The study provides valuable insights into how technology can be leveraged to promote economic development in Saudi Arabia by examining how API adoption can offer opportunities for digital transformation and economic growth.
The remainder of this paper is organized as follows: Section 2 reviews the relevant empirical literature, while Section 3 outlines the theoretical foundation. Section 4 develops the study’s hypotheses, and Section 5 details the research methodology and data sources. Section 6 presents the results and analysis, followed by a discussion in Section 7. Section 8 provides policy recommendations, Section 9 concludes the study, and Section 10 suggests directions for future research.

2. Empirical Review

According to empirical studies, APIs influence digital transformation and play a crucial role in the fields of business efficiency, financial inclusion and e-commerce [24]. Using firm-level data from the U.S., the author of [24] provides compelling evidence that API adoption is associated with a 15–20 per cent increase in operational efficiency, spreading through cost reduction and reduced speed of digital transactions. Similarly, the authors of [25], contend that, as infrastructures enable platform-based economies, APIs would allow firms to obtain scalability via the effortless composition of third-party services.
However, the existing research mainly focuses on developed economies with sophisticated technological ecosystems, regulatory support for data sharing, and advanced digital markets promoting API infrastructures. This geographic bias poses significant challenges to the generalizability of our findings to emerging economies, especially those with nascent regulatory landscapes, infrastructural deficiencies, and differing degrees of digital engagement. Moreover, the economic impact and scalability of APIs have been primarily discussed in the context of developed economies; the role of APIs in developing economies, especially in the Saudi Arabian context, with digital transformation still in progress, is largely underexplored. Interoperability constraints, cybersecurity risks, regulatory bottlenecks and limited developer ecosystems—among other headwinds—could substantially temper the anticipated virtues of API-driven innovation.
Additionally, the notion that API adoption maximally contributes to enhanced efficiency does not consider dependencies in context [26,27]. APIs enable financial inclusion in developed markets by allowing easier access to digital banking/payment services; however, these mechanisms may be inhibited in regions where the financial systems are fragmented or have data localization regulations [28,29]. Moreover, many API-enabled business models depend on network effects; therefore, there must be sufficient digital literacy and access for them to work effectively in developing markets [30,31].
Most empirical research shows that API usage positively correlates with e-commerce expansion. In Asia, the authors of [32] analyzed 500 e-commerce firms and documented that API integration delivered 35% improvements in customer retention rates and greater supply chain efficiency. The aforementioned API-enabled fintech avenues have led to greater e-commerce adoption within the Middle Eastern region, as has been the case with digital payments [33,34]. In Saudi Arabia, fintech applications based on APIs like STC Pay and HyperPay have revolutionized cashless transactions and underpinned the goal under Vision 2030 of increasing digital payments to reach 70% by 2025 [35]. Yet, research shows that regulatory hurdles, cybersecurity vulnerabilities, and lack of standardization impede API adoption, especially for small and medium-sized enterprises (SMEs) [36].
Gretczko et al. [37] provide strong evidence that API-based innovations significantly contribute to economic growth, accounting for an estimated 0.8–1.2% of aggregate GDP growth among OECD countries. This impact is due to productivity improvements, higher automation levels, and better data-driven decision-making. Likewise, API-driven cloud computing services in China have created over USD 65 billion in digital economic value in the past five years [38,39]—demonstrating how API ecosystems facilitate scalable and data-intensive business models. These results confirm that APIs provide technical uplift and underpin the acceleration of the digital economy [40,41].
However, whereas Saudi Arabia has made strategic investments of more than USD 15 billion in emerging technologies [7], the empirical relationship between API adoption and digital economy contributions remains largely underexplored. In contrast to the OECD and China, in which API infrastructures are integrated into highly developed digital economies, Saudi Arabia’s tech ecosystem remains in flux, with significant investments directed into artificial intelligence as well as blockchain technology and cloud computing. However, the contribution of APIs to economic outcomes in this ecosystem is still undetermined due to a lack of ingredient-level studies isolating the impact of APIs from trends in the ever-broadening phenomenon of digitalization across sectors [42,43].
This gap in research brings forth several serious questions. From the outset, most traditional analyses try to be all-encompassing, integrating API adoption into broader-scoped digital transformation frameworks, and as such, miss the quantification of its unique economic impact. This methodological limitation conceals how APIs generate industry-specific efficiencies, such as those in fintech, logistics, and e-commerce, where APIs enhance things like interoperability, financial inclusion, and supply chain optimization. Third, the potential for API-driven economic activity in Saudi Arabia is limited by other structural constraints, such as regulation, levels of digital literacy, and the development of the local developer ecosystem. In contrast, China’s business environment is highly connected, which has led to a manifold increase in cloud-based API integrations. At the same time, unlike China, Saudi Arabia’s digital economy remains in a developmental phase, which may well limit the immediate economic prospects associated with API adoption.

3. Theoretical Foundations of the API Economy

APIs can methodically be studied through multiple economic and technological lenses, such as the Technology Acceptance Model (TAM), Transaction Cost Economics (TCE), Platform Economy Theory and Endogenous Growth Theory. Such frameworks demonstrate that adopting APIs drives digital transformation, changes market circulatory systems, and leads to economic development studies.

3.1. Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) [19] is one of the core frameworks in technology adoption and is posited on two primary constructs: perceived usefulness and ease of use. Within the API economy, institutions employ APIs due to their potential to increase operational efficiency while lowering costs and enhancing customer experiences. As this model can indicate, the usability of APIs and their integration capabilities have largely contributed to exponential adoption across various industries. On the other hand, TAM is largely oriented to individual adoption/use behavior and has few macroeconomic implications, making it challenging to apply in the aggregate.

3.2. Transaction Cost Economics (TCE)

Transaction cost economics [20]—TCE—is based on the premise that firms minimize transaction costs when deciding between transactions or hierarchical formations. APIs drive down transaction costs, allowing for automated interactions between businesses and the removal of inefficiencies related to how data is exchanged and communicated. This aligns with how the digital economy is moving toward ever more decentralized and API-driven platforms. However, TCE does not account for network effects essential to API-based ecosystems.

3.3. Platform Economy Theory

Central to Platform Economy Theory [21] is the two-sided market structure prevalent on digital platforms, where Application Programming Interfaces (APIs) enable businesses and consumers to interact. APIs have enabled companies such as Amazon, Google, and Facebook to develop open platforms, a more innovative and growing ecosystem. DEEGA in Saudi Arabia also supports fintech and e-commerce, as well as governmental smart initiatives, enabling such efforts rapidly under the horizon of the 2030 digitization strategy. While this theory serves as an excellent base for understanding API-driven business models, it fails to recognize regulatory constraints, as well as data security, as necessary components of value exchange.

3.4. Endogenous Growth Theory

As one important example, Endogenous Growth Theory [22] contends that economic growth can be sustained through technological progress in the form of innovation and knowledge spillovers. APIs—an engine driving individual services like cloud computing, AI-based analytics, and embedded finance—help facilitate this process and increase productivity/economic output. This will be brought to reality under Saudi Arabia’s investment in emerging technologies, a testament to the strategic value of APIs in enhancing long-term digital economic growth in the Kingdom. However, this theory does not address more acute barriers to adoption, such as infrastructure and API monetization issues.

4. Hypothesis Development

4.1. API Adoption and the Digital Economy Index

Application Programming Interfaces (APIs) play a crucial role as the foundation of digital transformation, allowing various industries to integrate, automate, and innovate seamlessly. Previous studies show that adopting APIs will speed up the growth of the digital economy by improving the efficiency of business processes, accelerating technological innovations and creating new markets [37]. This process begins with internal and external business activities powered by APIs that allow for real-time, seamless data sharing between platforms, leading to enhanced interoperability and minimized operational costs that help build a strong digital economy [32]. With the digital transformation initiatives set forth under Vision 2030 in Saudi Arabia, APIs are the backbone for driving the digital infrastructure, fostering a robust e-commerce ecosystem, and expanding financial technology services [44]. With this perspective in mind, the following hypothesis is suggested:
H1. 
API adoption positively influences the digital economy index in Saudi Arabia.

4.2. API Adoption Rate and the Digital Economy Index

APIs drive the pace and scale of digital transformation. A high adoption rate positively correlates with innovation, service delivery, and user experience [45]. According to the literature, there is a direct correlation between economies that embrace API and the growth of many digital commerce, cloud computing, and fintech applications [46]. The Open Banking and Smart City initiatives in Saudi Arabia also depend on API adoption to ensure connectivity and automation [47]. Due to the crucial role played by APIs in the digitalization of the economy, the following hypothesis is proposed:
H1a. 
The API adoption rate has a positive and significant impact on the digital economy index in Saudi Arabia.

4.3. Number of Active APIs and the Digital Economy Index

This number indicates the level of interconnectedness of digital platforms and services through active APIs. An increasing number of APIs allows for greater data availability, enabling innovation ecosystems and improved business responsiveness [48]. Past empirics point to the fact that economies possessing a greater density of active APIs experience higher levels of e-commerce efficiency, adoption of digital payments, and usage of enterprise solutions [49]. The digital landscape in Saudi Arabia is rapidly changing with the increasing number of active APIs in various domains, such as banking, telecommunications, and e-government services [50]. Based on this, the following hypothesis is developed:
H1b. 
The number of active APIs positively affects the digital economy index in Saudi Arabia.

4.4. API Investment and the Digital Economy Index

API investments provide cybersecurity, optimize cloud services, and extend the potential development of the platform, driving the reinforcement of the digital economy [51]. According to research, investing in API ecosystems yields new forms of digital transactions, better customer experiences, and improved regulatory compliance [52]. As essential investments were made through the Vision 2030 program that encouraged API-oriented innovative solutions, fintech developments, and digital infrastructure, Saudi Arabia highlighted the significance of funding APIs in the economy [47]. From this, the following hypothesis is formed:
H1c. 
API investment contributes significantly to the digital economy index in Saudi Arabia.

5. Methodology and Data Sources

Using panel data analysis, this study provides a comprehensive empirical evaluation of the effects of API adoption on the digital economy in Saudi Arabia by assessing both the short-run and long-run impacts of API adoption [53]. Figure 1 explains the research framework.
Based on the research framework in Figure 1, the structural equation to examine the impact of Application Programming Interface (API) adoption on Saudi Arabia’s digital economy is as follows:
DEIit = α0 + β1 APIARit + β2 NAAPIsit+ β3 APIIit + εit
where DEI indicates the Digital Economy Index (DEI), which is assessed using the Digital Transformation Index score, E-commerce Growth (%), Digital Infrastructure Investment (Million SAR), and Digital GDP Contribution (%), with the expected impact remaining uncertain as is shown in the description of variables in Table 1. The Application Programming Interfaces Adoption Rate (APIAR) represents the percentage of businesses adopting APIs, with a potential positive or negative effect. Similarly, the Number of Active APIs (NAAPIs) in Saudi Arabia and API Investment (APII) in Million SAR reflecting investments in API-related projects are expected to positively or negatively influence the digital economy.
The primary justification for utilizing panel data in this study is their ability to measure the impact across a group rather than focusing on individual units [53]. In addition to combating heteroscedasticity, panel data are valuable when long-term data availability is scarce, which is often valid for developing countries and datasets based on repeated cross-sectional observations [53]. This study used a panel Autoregressive Distributed Lag (panel ARDL) model, an econometric method to estimate and examine both the short- and long-term relations [54]. Based on [55], the ARDL model allows for the inclusion of lagged values of dependent and independent variables, owing to the Granger causality of economic variables. This is especially valuable for the analysis of persistent and dependent variables. Moreover, given their potential for co-integration, dynamic relationships, endogeneity and non-stationarity, the ARDL method has been a popular econometric approach for practical empirical analysis [56].
The simplified ARDL (p, q, q, …, q) model is specified as follows:
Y i t = j = 1 p δ i Y i , t j + j = 0 q β   X i , t j + φ i + ε i t
Yit is the dependent variable, as (Xit) is a vector of r independent variables (Xit) where the vector should consist of (r = 0), (r = 1) process of [AR(0)] [AR(1)] and co-integration. δi is the coefficient of the lagged dependent variable, a scalar. Coefficients βij refer to the independent variable vector. The term φi captures unit-specific fixed effects, where i = 1,…, N is the cross-sectional dimension and t = 1,2,3, …, T is the time dimension. p and q indicate the optimal lag orders, and εit is the residual term, reflecting unobserved disturbances in the model.
The revised ARDL (p, q, q, q, …, q) error correction model is specified as follows:
Y i t = θ i Y i t 1 λ X i , t + j = 1 p 1 ξ i j   Y i t j + j = 1 p 1 β ij X i , t j + φ i + ε i t
Following the previous equation, y is the Digital Economy Index (DEI), the dependent variable, including lagged and differenced variables for short-term and long-term estimations, respectively. On the other hand, x represents the independent variable set, which includes both lagged values and differenced values of the independent variables, thereby accounting for the dynamic interactions within the model.
Missing values were addressed using linear interpolation for time-series continuity. Where interpolation was not feasible, mean substitution or last observation carried forward (LOCF) methods were applied to ensure data completeness and reliability. Further, the Digital Economy Index (DEI) is a composite measure derived from the Digital Transformation Index score, the annual growth rate of e-commerce, and the amount of digital infrastructure investment (in million SAR), capturing the multidimensional progress of the digital economy.

Data Collection and Sources

We analyzed critical digital economy variables regarding their measurement, expected impacts, and data sources. The Digital Economy Index (DEI) is our main dependent variable, which we evaluate using several different indicators. These include the Digital Transformation Index Score, which assesses the level of digital transformation within an economy; E-commerce Growth (%), representing the annual growth rate of e-commerce activities; Digital Infrastructure Investment (Million SAR), which captures financial investments directed toward digital infrastructure development; and Digital GDP Contribution (%), which measures the digital economy’s contribution to the overall Gross Domestic Product (GDP) [57]. The data for these indicators are sourced from the World Development Bank and Bloomberg, which provide reliable and comprehensive macroeconomic data relevant to digital transformation and economic development.
Alongside DEI, this research also includes measures related to the uptake of Application Programming Interfaces (APIs), which are increasingly seen as a key driver of digital economic expansion. The APIAR (Application Programming Interfaces Adoption Rate) is calculated as a percentage of the number of businesses that adopted APIs. Depending on how extensively and effectively APIs are integrated into various sectors, they can bring both positive and negative outcomes to the digital economy. Likewise, the number of active APIs (NAAPIs) in Saudi Arabia is treated as an independent variable, and the impact on the digital economy changes according to how much the APIs are utilized and the level of technology.
Additional analysis in the study focuses on API Investment (APII), indicating the investment of financial resources in API, measured in million SAR. The effect of investment in APIs may be positive or negative, depending on how much these investments are converted into better digital infrastructure, business efficiency, and economic growth. The data for API-related variables such as APIAR, NAAPIs, and APII come from Bloomberg, which tracks trends in technology adoption, investment flows and API-related developments across various industries [58]. By analyzing these key variables and using data from reputable sources, this study seeks to contribute to understanding the role of API adoption in shaping Saudi Arabia’s digital economy in both the short and long term.

6. Results and Analysis

6.1. Pre-Estimation Results

As presented in Table 2, the Digital Economy Index (DEI) has a mean of 0.000, which indicates that the data have been normalized. However, the standard deviation is high (0.559), which suggests high variability across different observations in levels of digital transformation. The DEI values ranging from −1.185 to 1.326 underscore the disparities, with some regions or sectors experiencing strong digital growth and others falling behind. APIAR averages 50.73%, meaning almost 50% of these companies have implemented APIs in their operations. Nonetheless, the high standard deviation (17.57%) suggests that there is essential diversity among adoption levels, where the values range from 20.85% to 79.41%. This variation indicates that while some industries or firms have embraced API-driven digital transformation, others remain hesitant or face barriers to adoption. Similarly, the number of active APIs (NAAPIs) shows a significant spread, with an average of 2896 APIs but a high standard deviation (1269 APIs). The minimum value (515 APIs) suggests limited API deployment in certain areas, whereas the maximum (4997 APIs) reflects highly digitalized ecosystems.
Investment in API-related projects (APII) also varies widely, with an average of 55.07 million SAR and values ranging from 10.07 million SAR to 98.22 million SAR. The high standard deviation (28.35 million SAR) suggests that API funding is not evenly distributed, with some sectors or firms heavily investing in API infrastructure while others allocate minimal resources.
Table 3 indicates that the correlation between the API adoption rate (APIAR) and the number of active APIs (NAAPIs) is −0.008, indicating an almost zero correlation. This suggests that the proportion of businesses adopting APIs does not have a direct linear relationship with the total number of active APIs. Though very small, the negative sign might suggest that businesses adopting APIs are not necessarily contributing to more active APIs, possibly due to differences in API usage intensity or sector-specific adoption patterns. The correlation between API adoption rate (APIAR) and API investment (APII) is 0.040, indicating a weak positive relationship. This suggests that higher investments in API-related projects are not strongly associated with increased adoption rates. This weak correlation could imply that while investments in APIs exist, they might not effectively translate into widespread adoption across businesses, possibly due to implementation challenges, lack of technical expertise, or slow integration processes.
The correlation between the number of active APIs (NAAPIs) and API investment (APII) is 0.018, also reflecting a very weak positive relationship. This suggests that increased investment in API-related projects does not necessarily lead to more active APIs. One possible explanation is that API investments might be concentrated on improving API security, efficiency, and infrastructure rather than directly increasing the quantity of APIs in the market. Additionally, API investments could be sector-specific, with some industries benefiting more than others.
The unit root test results in Table 4 reveal a mixed order of integration (I(0) and I(1)) among the variables, indicating different stationarity properties. The Digital Economy Index (DEI) and API Adoption Rate (APIAR) are non-stationary at the level but become stationary after first differencing (I(1)), suggesting that shocks to these variables have persistent effects over time. DEI exhibits a test statistic of −2.741 (p = 0.0620) at level, becoming stationary at first difference with −4.102 (p = 0.0185), while APIAR transitions from −3.821 (p = 0.2783) at level to −5.103 (p = 0.0018) after first differencing. Conversely, the Number of Active APIs (NAAPIs) and API Investment (APII) are already stationary at level (I(0)), with test statistics of −6.021 (p = 0.0000) and −3.589 (p = 0.0095), respectively, meaning their fluctuations are mean-reverting. The first difference values for NAAPIs and APII confirm strong stationarity, with test statistics of −7.982 (p = 0.0000) and −7.305 (p = 0.0000). These findings suggest that while API adoption and digital economy transformation follow long-term trends requiring differencing for stationarity, API investment and API activity levels are inherently stable. The presence of both I(0) and I(1) variables implies that further econometric testing, such as co-integration analysis (e.g., Johansen’s test), is necessary to explore potential long-term relationships among these variables in Saudi Arabia’s digital economy landscape.
The co-integration test results in Table 5 provide evidence of a long-term equilibrium relationship among the variables. The panel statistics show a v-statistic of −1.102, while the rho, t, and adf statistics are −3.289, −6.825, and −7.693, respectively. All these values suggest strong evidence against the null hypothesis of no co-integration. Similarly, the group statistics indicate a rho-statistic of −2.732, a t-statistic of −7.614, and an adf statistic of −8.859, further reinforcing the presence of co-integration. These continuously negative and significant test statistics indicate that we have a long-term relationship which allows the variables to move together all the time. The results suggest that API adoption, indicators of the digital economy, and levels of investment are not diverging through space but rather co-move with one another, realizing a cointegrated system. As such, the results support the application of error correction models (ECMs) or alternative long-term equilibrium modelling approaches to reflect such short-term dynamics and long-term relationships within the context of Saudi Arabia’s digital economy model.

6.2. Post-Estimation Results

The empirical results in Table 6 reveal a significant long-term positive correlation between API Adoption Rate (APIAR) and the Digital Economy Index (DEI), underscoring the transformative potential of APIs in advancing digital economies. This finding aligns well with the Technology Acceptance Model (TAM), where API adoption reflects perceived usefulness and ease of integration within organizational workflows. As businesses recognize APIs’ potential to enhance service delivery, interoperability, and innovation, their intention to adopt—and actual usage—increases, contributing to broader digital transformation. The data also support Endogenous Growth Theory, which emphasizes that technological innovation, such as APIs, acts as an internal engine for economic growth by increasing productivity and facilitating continual innovation across sectors.
The role of APIs as enablers of digital platforms further resonates with Platform Economy Theory. APIs facilitate scalability and multi-stakeholder connectivity, enabling ecosystem value creation through network effects. Their contribution to platform-based environments—where developers, service providers, and consumers interact—is a core mechanism through which digital economic activities are amplified. The significance of APIAR, in the long run, suggests that such platforms become more efficient and value-generating over time, reinforcing the notion that API-driven ecosystems are foundational to modern digital economies.
However, the absence of a statistically significant short-term effect for APIAR on DEI indicates a temporal lag in realizing economic benefits. This delay is particularly relevant in the context of Transaction Cost Economics (TCE). While APIs are designed to reduce transaction and coordination costs, their initial integration often involves high setup costs, complexity in technical implementation, and compliance with evolving regulatory frameworks. In emerging economies like Saudi Arabia, these challenges are intensified by the need for infrastructural upgrades, policy alignment, and the cultivation of skilled developer communities. These barriers help explain the muted short-term effects despite clear long-term advantages.
Further supporting this interpretation is the negative and statistically significant Error Correction Term (ECT) at the 9% level, indicating a gradual adjustment mechanism. If deviations occur in the DEI due to shocks in API adoption, the system gradually reverts to its long-term equilibrium, confirming the findings from Johansen’s co-integration theory. This reinforces the Endogenous Growth and Platform Economy perspectives, emphasizing that while the gains from API adoption are not immediate, they are enduring and cumulative—requiring consistent investments, policy reforms, and infrastructure development.
The results in Table 7 indicate that Net Active APIs (NAAPIs) have both short-term and long-term positive effects on the Digital Economy Index (DEI), supporting the Endogenous Growth Theory, which emphasizes the role of continuous innovation—such as API deployment—in driving sustained economic growth. The immediate impact reflects the direct contribution of active APIs to digital transformation, productivity, and service innovation.
The statistically significant Error Correction Term (ECT) at the 5% level confirms a long-term adjustment process, aligning with Platform Economy Theory, where APIs enable dynamic, scalable ecosystems that generate value over time. This result also reflects the Transaction Cost Economics (TCE) view, as APIs reduce coordination and processing costs, streamlining digital operations and facilitating more efficient market interactions.
From the Technology Acceptance Model (TAM) perspective, the widespread adoption and integration of APIs suggest high perceived usefulness and ease of use, both critical for sustained digital engagement. Altogether, the findings underscore APIs as strategic tools supporting immediate digital innovation and long-term structural economic growth.
The findings in Table 8 reveal that while API Investment (APII) positively influences the Digital Economy Index (DEI) in the short term, no significant long-term effect is observed. This supports the Endogenous Growth Theory, which emphasizes the importance of sustained innovation. The short-term gains—such as improved digital infrastructure, fintech expansion, and platform connectivity—highlight the value of API investments. However, the absence of a long-term impact suggests that without continuous innovation, ecosystem development, and strategic monetization, such investments may fail to drive enduring economic growth.
From a Platform Economy Theory perspective, the short-term rise in DEI reflects the role of APIs in enabling rapid technical integration, enhancing digital platforms, and connecting users and services. Yet, the lack of long-term effects points to systemic barriers like regulatory challenges, limited interoperability, and underdeveloped developer ecosystems that constrain the platform’s maturity over time.
The significant Error Correction Term (ECT) at the 5% level suggests that deviations from the long-term equilibrium are eventually corrected. This aligns with Transaction Cost Economics (TCE), indicating that APIs reduce coordination and transaction costs in the short term. However, persistent structural inefficiencies and a lack of ecosystem readiness may hinder the transition of short-term efficiencies into long-term value.
Lastly, the findings also relate to the Technology Acceptance Model (TAM). The short-term adoption of APIs likely stems from high perceived usefulness and ease of integration. Yet, consistent perceived value, supportive infrastructure, and favorable regulatory conditions are essential for long-term acceptance and economic impact.

7. Discussion

This study provides substantial evidence on the role of APIs in shaping digital economic development, revealing a nuanced distinction between short-term and long-term effects. API adoption demonstrates a statistically significant long-term impact on digital economy growth, aligning with theoretical expectations from the Platform Economy Theory and Endogenous Growth Theory. This finding underscores the strategic value of APIs as foundational digital infrastructure that support scalability, innovation, and interoperability over time. APIs facilitate more efficient digital transactions and platform-based ecosystems, contributing to sustained economic transformation.
However, the absence of a short-term effect from API adoption highlights an important temporal dynamic: the benefits of API integration are not immediate. This delay can be attributed to several real-world challenges, including the complexity of implementation, organizational inertia, and the time required to align APIs with broader digital transformation strategies. In emerging economies like Saudi Arabia, these challenges may be compounded by infrastructural gaps, limited technical capacity, or slower policy adaptation. As such, fully realizing digital economic benefits through APIs often requires a long gestation period, during which foundational capabilities must be cultivated.
Interestingly, while API adoption contributes to long-term gains, API-related investments yield measurable short-term benefits but do not appear to translate into lasting improvements in digital economic performance. This divergence raises critical questions about investment efforts’ strategic direction and efficiency. Short-term boosts may stem from immediate infrastructure upgrades or the initial launch of API-enabled services, such as in fintech, cloud platforms, or e-commerce. Yet without sustained adoption, organizational integration, or ecosystem development, these investments risk being one-off enhancements rather than engines of continuous growth. This finding signals a need for policy and institutional frameworks that prioritize expenditure and ongoing usage, capacity building, and innovation ecosystems.
A key limitation of the study lies in its exclusive focus on Saudi Arabia. While the country presents a compelling case of digital ambition and investment, its unique socio-economic and regulatory environment limits the generalizability of the findings. The pace and impact of API adoption can differ markedly across countries, depending on factors such as market openness, infrastructure maturity, and policy coherence. Consequently, future research should consider comparative analyses across regions or economies at different stages of digital development to validate the broader applicability of these insights.
Additionally, several moderating factors warrant closer attention. Digital literacy, for instance, plays a pivotal role in determining how effectively APIs are utilized across the economy. In contexts where digital skills are unevenly distributed, adopting API-driven tools may be confined to tech-savvy firms or urban populations, limiting broader economic impact. Sectoral differences are also critical. The private sector, driven by competitive incentives, may adopt APIs more aggressively and innovate faster, whereas the public sector may encounter procedural delays and legacy system constraints that slow integration. Understanding these intra-country differences can show where policy interventions are most needed.

8. Policy Recommendations

The need to foster sustainable long-term API ecosystems is alerted by the lagging effect of API Adoption Rate (APIAR) on the Digital Economy Index (DEI), suggesting improving long-term API integration plans. This is aligned with SDG 9. SDG 9 is about Industry, Innovation, and Infrastructure. On the policy side, offer grants and tax advantages to companies that adopt APIs, invest in training developers, and establish standards for APIs to increase interoperability and economic productivity.
Likewise, NAAPIs significantly influence DEI both in the short and long term, justifying the need for fast-tracked short-term API deployment. Especially for fintech, e-commerce, and government services sectors, policymakers should cut approval processes to onboard APIs in new and innovative ways and for more rapid realization of digital transformation benefits. This advances SDG 8: Decent Work and Economic Growth by enhancing employment based on innovation while promoting digital entrepreneurship. Moreover, creating regulatory sandboxes will foster inclusive economic growth because it will provide businesses with a controlled environment to test API-driven solutions and scale them efficiently.
Furthermore, API Investment Strategies must be more targeted as API Investment (APII)’s impact on DEI is short-term. Investing not only in API development but also in strong infrastructure, cybersecurity, AI-powered API building, and cloud computing will enhance long-term digital growth with policymakers. In line with SDG 17: Partnerships for the Goals, public–private partnerships should be incentivized to drive the scaling of digital infrastructure and strengthen technological R&D beyond borders, enabling sustainable and disruptive API ecosystems.
Investing in developer ecosystems is also acute to address the limited long-term rate of return of API investments. They can support open API marketplaces, create developer incentives and organize hackathons and innovation labs. This aligns with the goal of SDG 4: Quality Education, which promotes digital literacy and technical skills—that developers have the necessary skills and opportunity to create scalable, innovative solutions. A strong developer ecosystem will enable API adoption and enhanced continuous digital innovation.
Ultimately, the positive impacts of API integration must be bolstered by stronger regulatory support and standardization. Finally, including the Error Correction Term (ECT) demonstrates the importance of establishing regulatory frameworks across the board, addressing one of the world’s most significant challenges, as mentioned in SDG 16: Peace, Justice and Strong Institutions. Industry standards would guide API development, and data security and privacy measures would ensure safe operations. At the same time, a centralized API governance body would need to be created to ensure compliance and facilitate innovation across sectors. Such efforts will provide transparency, accountability, and seamless integration of APIs into the digital economy. Thus, by applying these policy recommendations, Saudi Arabia could export APIs as technical solutions and strategic enablers of digital economic growth to maximize innovation and productivity whilst ensuring that the country inextricably follows the UN’s SDGs and Vision 2030.

9. Conclusions

This study examined the impact of API adoption on Saudi Arabia’s digital economy. The positive long-term effect of the API Adoption Rate (APIAR) on Digital Economy Index (DEI) through a panel Autoregressive Distributed Lag (ARDL) approach on monthly data from the period 2015 to 2024, extracted from the World Development Indicators and Bloomberg, reflects the role of APIs in changing the nature of work and economic performance by improving innovation, enabling companies to implement business at scale, and seamlessly transition to online commerce; this outcome directly contributes to Sustainable Development Goal 9: Industry, Innovation and Infrastructure. The extended timeline for these benefits highlights the importance of continued investment in resilient digital ecosystems, the principles of interoperability, and the development of more advanced technological infrastructure. In addition, it also confirms the short-term and long-term positive impacts of the Number of Active APIs (NAAPIs) on DEI, which shows that it takes time for active APIs to contribute to the economic development process, but their contribution will be sustained. Driving DTAAP helps fast-track strategies aligned with SDG 8: Decent Work and Economic Growth through innovation-driven job opportunities and improves world entrepreneurship through API-enabled platforms. The immediate injection of hyperactive APIs propels fintech, e-commerce, and simultaneous cloud services in concert, reducing barriers to entry while stimulating holistic participation in the economic and technological realms. Short-term returns may not indicate a lasting connection with long-term success; therefore, APII’s effect on DEI must remain focused on the short term, with minimal long-lasting significance. This finding is particularly relevant to SDG 17: Partnerships for the Goals, emphasizing the critical role of public–private partnerships in improving digital infrastructure, strengthening cybersecurity, and enabling AI-enabled solutions. API investments with long-term effects are not felt immediately; hence, partnerships become essential to ensure continuous reinvestment in the ecosystem for development. A key limitation of this study is its exclusive focus on Saudi Arabia, which may restrict the generalizability of the findings to other countries with different digital maturity levels, regulatory environments, or socio-economic conditions; additionally, the use of secondary data sources may limit the depth of insight into organizational-level API strategies, while the panel ARDL approach, though effective for assessing dynamic relationships, may not fully capture the influence of contextual or qualitative factors such as digital literacy, developer ecosystem readiness, or sector-specific API adoption patterns.

10. Future Research Directions

Further studies can include industry-specific analyses to explore how API adoption can shape the fintech, e-commerce, and smart city domains in Saudi Arabia—potentially offering a blueprint for other industries in their digital transformation journey. It would also be interesting to study APIs comparatively between countries, to understand how API ecosystems in Saudi Arabia compare with other emerging economies, document best practices, and highlight gaps. Lastly, longitudinal studies on API adoption, active API ecosystems and investment over time can guide how the relationship between APIs and the Digital Economy Index (DEI) evolves to remain aligned with Saudi Arabia’s Vision 2030 and the UN’s Sustainable Development Goals (SDGs).

Author Contributions

M.A.A.: Writing—original draft, Formal Analysis, Methodology; S.M.S.: Conceptualization, Methodology, Writing—review and editing, Administration. All authors have read and agreed to the published version of the manuscript.

Funding

This Project is sponsored by Prince Sattam bin Abdulaziz University (PSAU).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used in preparing this manuscript are available from the corresponding author upon reasonable request.

Acknowledgments

The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through project number (PSAU/2024/02/32008).

Conflicts of Interest

The authors declare that they do not have any conflicts of interest.

References

  1. Gartner. The API Economy: How APIs Drive Digital Business Innovation. In Gartner Reports; Gartner: Stamford, CT, USA, 2022. [Google Scholar]
  2. Duong, M.P.; Le, M.H.; Nguyen, T.T.; Duong, M.Q.; Doan, A.T. Economic and Technical Aspects of Power Grids with Electric Vehicle Charge Stations, Sustainable Energies, and Compensators. Sustainability 2025, 17, 376. [Google Scholar] [CrossRef]
  3. Chikri, H.; Kassou, M. Financial Revolution: Innovation Powered by Fintech and Artificial Intelligence. J. Theor. Appl. Inf. Technol. 2024, 102, 4145–4157. [Google Scholar]
  4. MarketsandMarkets. API Management Market Size, Trends, and Growth Forecast (2022–2027). In MarketsandMarkets Reports; MarketsandMarkets: Pune, India, 2023. [Google Scholar]
  5. Rehan, H. Revolutionizing America’s Cloud Computing: The Pivotal Role of AI in Driving Innovation and Security. J. Artif. Intell. Gen. Sci. (JAIGS) 2024, 2, 239–240. [Google Scholar]
  6. Abubakr, A.A.M.; Khan, F.; Mohammed, A.A.A.; Abdalla, Y.A.; Mohammed, A.A.A.; Ahmad, Z. Impact of AI Applications on Corporate Financial Reporting Quality: Evidence from UAE Corporations. Qubahan Acad. J. 2024, 4, 782–792. [Google Scholar]
  7. Arab News. Saudi Arabia Invests over $15 Billion in Emerging Technologies. Arab News, 15 March 2023. [Google Scholar]
  8. Saudi Ministry of Communications and Information Technology (MCIT). Saudi Arabia’s ICT Sector Contribution to GDP and Digital Transformation Initiatives. In MCIT Reports; MCIT: Riyadh, Saudi Arabia, 2023. [Google Scholar]
  9. Saudi Data and AI Authority (SDAIA). National AI Strategy and API Adoption in Saudi Arabia. In SDAIA Reports; SDAIA: Riyadh, Saudi Arabia, 2023. [Google Scholar]
  10. Finextra. Saudi Arabia Emerges as MENA’s Leading FinTech Hub with Rapid API Adoption. In Finextra; Finextra Research Ltd.: London, UK, 2023. [Google Scholar]
  11. Rastogi, S.; Goel, A.; Doifode, A. Open API in Indian Banking and Economic Development of the Poor: Opportunities and Challenges. Int. J. Electron. Bank. 2020, 2, 321–348. [Google Scholar] [CrossRef]
  12. McKinsey & Company. China’s Digital Economy: Powering the Economy to Global Competitiveness. In McKinsey Global Institute Reports; McKinsey & Company: New York, NY, USA, 2022. [Google Scholar]
  13. Cheng, Y.W.; Bilal, A. Regulatory Data Privacy Concerns in Proliferating IoT Era of Telecommunication Data Monetization: A Systematic Literature Review. In Authorea Preprints; Wiley: New York, NY, USA, 2024. [Google Scholar]
  14. World Bank. Digital Transformation and Economic Growth in Emerging Markets: The Role of APIs. In World Bank Reports; World Bank: Washington, DC, USA, 2023. [Google Scholar]
  15. Heshmatisafa, S.; Seppänen, M. Exploring API-Driven Business Models: Lessons Learned from Amadeus’s Digital Transformation. Digit. Bus. 2023, 3, 100055. [Google Scholar] [CrossRef]
  16. Saudi Vision 2030. Vision 2030 and Saudi Arabia’s Digital Transformation Agenda. In Saudi Vision 2030 Reports; Saudi Vision 2030: Riyadh, Saudi Arabia, 2023. [Google Scholar]
  17. Arab News. Saudi Arabia’s Digital Economy Contributes 14% to GDP: Survey. Arab News, 29 February 2024. [Google Scholar]
  18. DataTechVibe. Here’s Why Saudi Arabia Is a Digital Riser. In DataTechVibe; MartechVibe Media: Dubai, United Arab Emirates, 2024. [Google Scholar]
  19. Davis, F.D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Manag. Inf. Syst. Q. 1989, 13, 319–340. [Google Scholar] [CrossRef]
  20. Williamson, O.E. The Economics of Organization: The Transaction Cost Approach. Am. J. Sociol. 1981, 87, 548–577. [Google Scholar] [CrossRef]
  21. Rochet, J.-C.; Tirole, J. Platform Competition in Two-Sided Markets. J. Eur. Econ. Assoc. 2003, 1, 990–1029. [Google Scholar] [CrossRef]
  22. Romer, P.M. Endogenous Technological Change. J. Political Econ. 1990, 98, S71–S102. [Google Scholar] [CrossRef]
  23. Weber, B.W.; Kauffman, R.J. On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. J. Manag. Inf. Syst. 2018, 35, 10–48. [Google Scholar]
  24. Fang, D. The Causal Effect of Data Production Factor Adoption on Company Performance. Front. Environ. Sci. 2022, 10, 939243. [Google Scholar]
  25. Evans, D.S.; Schmalensee, R. Matchmakers: In The New Economics of Multisided Platforms; Harvard Business Review Press: Boston, MA, USA, 2016. [Google Scholar]
  26. Serbout, S.; Pautasso, C. How Are Web APIs Versioned in Practice? A Large-Scale Empirical Study. J. Web Eng. 2024, 23, 465–506. [Google Scholar] [CrossRef]
  27. Bin Hidthir, M.H.; Khan, A.A.; Junoh, M.Z.M.; Yusof, M.F.B.; Ahmad, Z. Development of the Financial Composite Index for MENA Region: A Two-Staged Principal Components Analysis. SAGE Open 2025, 15, 21582440251320484. [Google Scholar] [CrossRef]
  28. Ahmad, Z.; Bin Hidthiir, M.H.; Rahman, M.M.; Junoh, M.Z.M.; Yusof, M.F.B. Impact of TBL-Based CSR Disclosure on Financial Performance in Halal Food Companies: A System GMM Analysis. SAGE Open 2025, 15, 21582440241296659. [Google Scholar] [CrossRef]
  29. Boyd, M.; Vaccari, L.; Posada, M.; Gattwinkel, D. An Application Programming Interface (API) Framework for Digital Government; European Commission, Joint Research Centre: Brussels, Belgium, 2020. [Google Scholar]
  30. Bin Hidthiir, M.H.; Ahmad, Z.; Lun, L.K.; Mansur, M.; Abubakr, A.A.M.; Sahal, M.S.G. Determinants of Government Debt in ASEAN-5 Nations: An ARDL Analysis of Economic Factors. Qubahan Acad. J. 2024, 4, 250–267. [Google Scholar] [CrossRef]
  31. Jiang, X.; Zhang, Y.; Wang, L. API-Driven Economic Growth: Evidence from Digital Economies. Digit. Transform. Rev. 2022, 14, 55–72. [Google Scholar]
  32. Alam, N. FinTech and Islamic Finance: Digitalization. In Development, and Disruption; Palgrave Macmillan: London, UK, 2023. [Google Scholar]
  33. Ahmad, Z.; Hidthiir, M.H.B.; Rahman, M.M. Impact of CSR Disclosure on Profitability and Firm Performance of Malaysian Halal Food Companies. Discov. Sustain. 2024, 5, 18. [Google Scholar] [CrossRef]
  34. Saudi Central Bank. Annual Report 2023; Saudi Central Bank: Riyadh, Saudi Arabia, 2023. Available online: https://www.sama.gov.sa (accessed on 29 January 2025).
  35. World Bank. The Role of APIs in Digital Transformation; World Bank Publications: Washington, DC, USA, 2023; Available online: https://www.worldbank.org (accessed on 22 February 2025).
  36. Laplante, P.; Zhang, J.; Voas, J. The API Economy and Its Impact on Software Development. IEEE Softw. 2020, 37, 60–67. [Google Scholar]
  37. Khan, A.A.; Hidthiir, M.H.B.; Wah, T.B. Nonlinear Impact of Remittances on Financial Inclusion in Developing Countries: Does Governance Quality Matter? Pak. J. Commer. Soc. Sci. (PJCSS) 2024, 18, 811–831. [Google Scholar]
  38. McKinsey. The Role of APIs in Enabling Digital Transformation and Economic Growth; McKinsey & Company: New York, NY, USA, 2022; Available online: https://www.mckinsey.com (accessed on 7 February 2025).
  39. Khan, S.A.R.; Sheikh, A.A.; Shamsi, I.R.A.; Yu, Z. The Implications of Artificial Intelligence for Small and Medium-Sized Enterprises’ Sustainable Development in the Areas of Blockchain Technology, Supply Chain Resilience, and Closed-Loop Supply Chains. Sustainability 2025, 17, 334. [Google Scholar] [CrossRef]
  40. Hidthiir, M.H.B.; Ahmad, Z.; Junoh, M.Z.M.; Yusof, M.F.B. Dynamics of Economic Growth in ASEAN-5 Countries: A Panel ARDL Approach. Discov. Sustain. 2024, 5, 145. [Google Scholar] [CrossRef]
  41. Benzell, S.G.; Hersh, J.; Van Alstyne, M. How APIs Create Growth by Inverting the Firm. Manag. Sci. 2024, 70, 7120–7141. [Google Scholar] [CrossRef]
  42. Rahman, M.M.; Ahmad, Z.; Mokal, M.N.; Aziz, M.F.; Khotib, N.A.M. Green Sustainability and Financial Performance of Halal Food Companies: Evidence of Malaysia. J. Islam. Monet. Econ. Financ. 2024, 10, 709–734. [Google Scholar] [CrossRef]
  43. Al-Naimi, A.A.; Al Abed, S.; Farooq, U.; Qasaimeh, G.; Alnaimat, M.A. Impact of Open Banking Strategy and Fintech on Digital Transformation. In Proceedings of the 2023 International Conference on Business Analytics for Technology and Security (ICBATS), Dubai, United Arab Emirates, 6–7 March 2023; pp. 1–5. [Google Scholar]
  44. Hein, A.; Schreieck, M.; Wiesche, M.; Krcmar, H. The Impact of API Adoption on Digital Business Models. J. Inf. Syst. Technol. 2019, 87–103. [Google Scholar]
  45. Mukhopadhyay, S.; Krishnan, R.; Grover, V. API Ecosystems and the Evolution of Digital Economies. Inf. Syst. Res. 2021, 987–1003. [Google Scholar]
  46. Alshamrani, S. Investment in API-Driven Digital Infrastructure: Case Study of Saudi Arabia. Middle East J. Technol. Innov. 2022, 102–118. [Google Scholar]
  47. Benlian, A.; Hilkert, D.; Hess, T. How Open APIs Drive Digital Transformation: The Case of Platform-Based Business Models. Manag. Inf. Syst. Q. 2020, 567–590. [Google Scholar]
  48. Teece, D.J. Business Models and Dynamic Capabilities in the Digital Economy. In Long Range Planning; Elsevier: Amsterdam, The Netherlands, 2018; pp. 40–49. [Google Scholar]
  49. Alghamdi, A.; Beloff, N. The Role of Digital Transformation in Saudi Arabia’s Economic Development. J. Digit. Econ. 2021, 45–61. [Google Scholar]
  50. Weber, B.W.; Kauffman, R.J. The Economic Value of APIs in Digital Business. In Electronic Markets; Springer: Berlin, Germany, 2019; pp. 37–53. [Google Scholar]
  51. Zachariadis, M.; Ozcan, P. The API Economy and Financial Services: The Case of Open Banking. J. Financ. Transform. 2017, 127–142. [Google Scholar]
  52. Karabiyik, H.; Palm, F.C.; Urbain, J.P. Econometric Analysis of Panel Data Models with Multifactor Error Structures. Annu. Rev. Econ. 2019, 495–522. [Google Scholar] [CrossRef]
  53. Behera, J.; Mishra, A.K. Renewable and Non-Renewable Energy Consumption and Economic Growth in G7 Countries: Evidence from Panel Autoregressive Distributed Lag (P-ARDL) Model. In International Economics and Economic Policy; Springer: Berlin, Germany, 2020; pp. 241–258. [Google Scholar]
  54. Nkoro, E.; Uko, A.K. Autoregressive Distributed Lag (ARDL) Co-integration Technique: Application and Interpretation. J. Stat. Econom. Methods 2016, 5, 63–91. [Google Scholar]
  55. Rahman, M.M.; Islam, A.M. The Autoregressive Distributed Lag (ARDL) Methodology in Estimating Dynamic Models: An Application to Stock Price and Exchange Rate Nexus in Malaysia. Int. J. Financ. Res. 2020, 440–450. [Google Scholar]
  56. Gretczko, M.; Ewenstein, B.; Bolognese, A. The API Economy: Disruption and the Business of APIs. In Deloitte Insights; Deloitte: New York, NY, USA, 2020. [Google Scholar]
  57. Elliott, J.; Holland, J.; Thomson, R. Longitudinal and Panel Studies. In The SAGE Handbook of Social Research Methods; SAGE Publications: London, UK, 2008; pp. 228–248. [Google Scholar]
  58. Khanyi, M.B.; Xaba, S.N.; Mlotshwa, N.A.; Thango, B.; Matshaka, L. A Roadmap to Systematic Review: Evaluating the Role of Data Networks and Application Programming Interfaces in Enhancing Operational Efficiency in Small and Medium Enterprises. Sustainability 2024, 16, 10192. [Google Scholar] [CrossRef]
Figure 1. Research framework.
Figure 1. Research framework.
Sustainability 17 04104 g001
Table 1. Description of variables.
Table 1. Description of variables.
VariableMeasurementExpected Result
DEIDigital Economy Index (DEI) =
Digital_Trans_Index: Digital transformation index score.
E-commerce Growth (%): Annual growth rate of e-commerce.
Digital_Infra_Investment (Million SAR): Investments in digital infrastructure.
Digital GDP Contribution (%): Digital economy’s contribution to GDP.
?
APIARApplication Programming Interfaces (APIs) Adoption Rate = Percentage of businesses adopting APIs.−/+
NAAPIsNumber of active APIs in KSA.−/+
APIIAPI Investment (Million SAR): Investment in API-related projects.−/+
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
VariableObs.MeanStd. Dev.MinMax
DEI12000.559−1.1851.326
APIAR12050.72917.57220.85279.411
NAAPIs1202896.7251269.9965154997
APII12055.07428.34710.06798.218
Table 3. Matrix of correlations.
Table 3. Matrix of correlations.
Variables(1)(2)(3)
APIAR1.000
NAAPIs−0.0081.000
APII0.0400.0181.000
Table 4. Unit root test.
Table 4. Unit root test.
VariableTrend and InterceptOrder of Integration
LevelFirst Difference
DEI−2.741 * (0.0620)−4.102 ** (0.0185)I(1)
APIAR−3.821 (0.2783)−5.103 *** (0.0018)I(1)
NAAPIs−6.021 *** (0.0000)−7.982 *** (0.0000)I(0)
APII−3.589 ** (0.0095)−7.305 *** (0.0000)I(0)
Table 5. Co-integration.
Table 5. Co-integration.
Test Stats.PanelGroup
v−1.102
rho−3.289−2.732
t−6.825−7.614
adf−7.693−8.859
Table 6. Impact of APIAR on DEI.
Table 6. Impact of APIAR on DEI.
D.DEICoef.Std. ErrzP > |z|
LR
APIAR0.00045890.01256190.040.071
SR
ECT−0.98626530.104689−9.420.000
APIAR (D1)0.00106660.00442330.240.809
_cons0.04824820.41732220.120.908
Pooled Mean Group Estimation: Error
Number of obs. = 120
Table 7. Impact of NAAPIs on DEI.
Table 7. Impact of NAAPIs on DEI.
D.DEICoef.Std. ErrzP > |z|
LR
NAAPIs0.00010480.00004872.150.031
SR
ECT−1.0549040.1064998−9.910.000
NAAPIs (D1)0.00005730.00002122.700.007
_cons−0.3028020.0598899−5.060.000
Pooled Mean Group Estimation: Error
Number of obs. = 120
Table 8. Impact of APII on DEI.
Table 8. Impact of APII on DEI.
D.DEICoef.Std. ErrzP > |z|
LR
APII0.00292730.00213941.370.171
SR
ECT−1.0543650.0980393−10.750.000
APII (D1)0.00354130.00180651.960.050
_cons0.1826430.06208592.940.003
Pooled Mean Group Estimation: Error
Number of obs. = 120
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ali, M.A.; Salih, S.M. Impact of Application Programming Interfaces (APIs) Economy on Digital Economics in Saudi Arabia. Sustainability 2025, 17, 4104. https://doi.org/10.3390/su17094104

AMA Style

Ali MA, Salih SM. Impact of Application Programming Interfaces (APIs) Economy on Digital Economics in Saudi Arabia. Sustainability. 2025; 17(9):4104. https://doi.org/10.3390/su17094104

Chicago/Turabian Style

Ali, Mohamed Ali, and Sara Mohamed Salih. 2025. "Impact of Application Programming Interfaces (APIs) Economy on Digital Economics in Saudi Arabia" Sustainability 17, no. 9: 4104. https://doi.org/10.3390/su17094104

APA Style

Ali, M. A., & Salih, S. M. (2025). Impact of Application Programming Interfaces (APIs) Economy on Digital Economics in Saudi Arabia. Sustainability, 17(9), 4104. https://doi.org/10.3390/su17094104

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop