Introduction

In today’s complex market environment, firms are facing unprecedented multiple challenges. From public health emergencies to unpredictable geopolitical patterns to increasingly severe climate disasters, the constant evolution of these external factors makes business development full of uncertainty. Against this backdrop, how to learn to survive and preserve themselves in a crisis has become an important issue for firms. In the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) business environment (Bennett and Lemoine 2014), organizational agility - the ability to perceive, respond and adapt to rapid environmental change - has become an important factor affecting the survival and success of firms (Saputra et al. 2022). Therefore, how to shape and enhance organizational agility has become a common focus of the current practical and academic communities (Ferraris et al. 2022; Gao et al. 2020).

Digitalization refers to the process of embedding digital technologies into organizational processes and routines, resulting in new ways of operating and coordinating activities (Legner et al. 2017; Tilson et al. 2010). It involves more than just the adoption of digital tools—it reflects the broader sociotechnical integration of digital capabilities that reshape how firms communicate, process information, and allocate resources. Within increasingly volatile business environments—characterized by prolonged public health crises like COVID-19, rising geopolitical tensions, and early signs of deglobalization—digitalization is seen as a key enabler of organizational responsiveness and flexibility (AlNuaimi et al. 2022; Sambamurthy et al. 2003). By enabling real-time visibility, enhanced coordination, and adaptive reconfiguration, digitalization can support firms in improving their organizational agility.

Although there is continuous attention to the influence of digitalization on corporate performance, certain research gaps still exist. First, there is a lack of studies investigating the potential influence of digitalization on organizational agility. Organizational agility is a crucial capability for companies to adapt to changes in their environment and implement innovation promptly (Swafford et al. 2006; Kalaignanam et al. 2021). This ability enables them to respond swiftly to unexpected changes and sustain their competitive edge (Rapaccini et al. 2020; Nazir and Pinsonneault 2012). At present, the majority of research is focused on leadership styles (Aurélio de Oliveira et al. 2012; AlNuaimi et al. 2022), knowledge management capabilities (Haider and Kayani 2020; Cegarra-Navarro and Martelo-Landroguez 2020; Harsch and Festing 2020; Idrees et al. 2022; Mao et al. 2015), and others, with less research from a digital perspective. Second, based on the contextual nature of the research, we find that the majority of the literature on organizational agility (Harsch and Festing 2020; Roberts and Grover 2012) focuses on normal situations rather than thoroughly examining the factors that contribute to organizational agility in crisis situations, particularly when abrupt public events are involved. Typically, agility is even more important for firms in critical situations. They need to have stronger flexibility to adapt to new situations and challenges brought about by crises. Third, although existing literature has noted the heterogeneity of digital platforms and studied their different forms (Gawer et al. 2002; Gawer and Cusumano 2008), research on how the extent of firms’ participation across multiple platforms impacts their organizational outcomes still needs to be enriched. In addition, individual differences caused by the strength of corporate competitiveness are often overlooked by researchers, which is precisely one of the reasons that may lead to different performance of different firms (Kwak et al. 2019). Finally, most studies on the impact of digitalization on corporate behavior have conducted scenario embedding research, and some scholars have measured the digital transformation of enterprises. However, they usually extract samples from listed companies or other publicly disclosed large and medium-sized companies, ignoring small and medium-sized enterprises in various industries. Under the impact of sudden public events, small and medium-sized enterprises have become relatively vulnerable entities facing development challenges (Ashiru et al. 2022). Therefore, it is necessary to pay more attention to the development of small and medium-sized enterprises and provide a more comprehensive perspective on the role of digitalization in enterprises.

To address these research gaps, we aim to investigate the following specific research questions:

  • How do digitalization affects organizational agility?

  • How do platform and firm competitiveness moderate this impact?

To test these predictions, we use real and objective enterprise survey data to analyze the impact of digitalization on organizational agility. The study utilized data from Enterprise Survey for Innovation and Entrepreneurship in China (ESIEC). Through a combination of theoretical analysis and empirical testing, we obtain consistent and robust results explaining the positive impact of digitalization on organizational agility and that this impact is negatively moderated by the number of platform participants and firm competitiveness.

The findings add valuable insights to existing literature in several ways. Firstly, this research pioneers the connection between digitalization studies and organizational agility literature, which enhances our comprehension of how digitalization functions, especially in the context of external shocks such as pandemics, geopolitical disruptions, or climate-related crises. Secondly, whereas previous studies have ignored the number of digital platforms participated in and individual differences caused by the strength of firms’ competitiveness, our study goes beyond these studies by exploring the moderating roles of digital platforms and firms’ competitiveness. In addition, since our study focuses on MSMEs and is based on field survey data, we can provide empirical data support for the impact of digitalization on organizational agility with real and valid sample data, and provide actionable insights for managers seeking to leverage digitalization to enhance organizational agility in an increasingly uncertain world.

In the following section, we profile the theoretical background for this study and develop research hypotheses. Subsequently, we detail the data set and models, followed by the presentation of empirical results. Finally, we conclude by discussing both the theoretical and practical implications of our findings, along with addressing limitations encountered.

Literature review

Digitalization

Digitalization is a critical driver of global economic growth(Calderon-Monge and Ribeiro-Soriano 2024). Spurred by the emergence and widespread adoption of the internet, along with the rapid advancement of related technologies, the process of digitalization has accelerated significantly. Broadly defined, digitalization involves integrating digital technologies into business processes, operations, and strategies to create value and enhance performance (Vial 2019). Enterprise digitalization is an important micro form of the digital economy, and studies by scholars have shown that promoting digitalization will have a good economic effect on the development of enterprises, not only helping to overcome the problems of high transaction costs (ElMassah and Mohieldin 2020), information asymmetry (Guo et al. 2024; Ivanov et al. 2019) and other pain points of traditional enterprises, but also improving the production mode and business model of enterprises (Warner and Wäger 2019), reduce financing costs (Jiang et al. 2022), improve enterprise productivity (Lin et al. 2024) and product quality (Westerman 2016), and enhance enterprise economic value (Li et al. 2021).

Digitalization involves multiple dimensions of enterprise operations and production. The digital operations dimension focuses on Internet-based applications to streamline business processes and improve connectivity. The business model in which firms obtain orders via the Internet is defined as e-commerce, and e-commerce technologies have been found in the literature to break the time-space constraints of traditional transactions, change the place where transactions take place, expand transaction time, and improve transaction efficiency (Erik and Hitt 2000). The digital production dimension emphasises the use of advanced digital machines, such as industrial robots and 3D printing, to increase production capacity. Research has shown that digital production not only reduces costs, but also increases flexibility and customisation in manufacturing (Porter and Heppelmann 2015).

While existing studies have greatly improved our understanding of digitalization, they are often based on samples drawn from listed companies, high-tech firms or medium to large companies with established patents and public recruitment data. These samples, while valuable, tend to emphasise companies with strong resources and advanced digital capabilities, and fail to cover MSMEs and firms in wider industries. MSMEs often encounter unique constraints, such as limited operational resources, technical expertise and workforce capacity, which can have a significant impact on their digital trajectory and outcomes. By focusing on the digitalization of MSMEs, the study provides a more holistic view of the role of digitalization in business.

Organizational agility

Organizational agility theory has received significant attention and scholarly investigation. Organizational agility refers to a firm’s capacity to identify and respond to innovation possibilities or market pressures by efficiently obtaining and integrating the required knowledge, assets, and relationships (Sambamurthy et al. 2003; Ashrafi et al. 2019). This definition emphasizes agility as a dynamic capability, distinguishing it from organizational flexibility. Agility emphasizes proactive and dynamic responses, focusing on seizing opportunities and preemptively navigating risks in uncertain environments. In contrast, flexibility is primarily reactive, reflecting an organization’s ability to adapt to changes or disturbances after they occur (Lee et al. 2015; Phillips and Tuladhar 2000).

Furthermore, the concept of agility in this paper is closely linked to organizational resilience in crisis situations. They are related yet distinct constructs, often discussed in tandem when examining organizational responses to crises. Agility focuses on adaptability and rapid response, highlighting an organization’s ability to pivot strategies or operations to capture opportunities and mitigate risks in real time (Felipe et al. 2016; Mao et al. 2023). It is forward-looking, emphasizing speed and precision in managing uncertainty. Resilience, by contrast, centers on absorbing shocks and recovering. It reflects an organization’s capacity to endure disruptions and restore stability, even under adverse conditions (Abidi et al. 2022; Copestake et al. 2024).

Organizational agility manifests through both structural and managerial dimensions. Agile organizational structures refer to flexible hierarchies, decentralized decision-making, and cross-functional teams, enabling rapid adaptation to market and environmental changes (Bouguerra et al. 2021; Carvalho et al. 2019; Duvivier and Gupta 2023). These structures reduce bureaucracy and foster innovation by enhancing communication and collaboration across the firm (Tallon and Pinsonneault 2011).

Agile management tools, such as Scrum, Kanban, and design thinking, complement these structures by facilitating iterative decision-making, continuous feedback loops, and adaptive project management (Sravan et al. 2024). These tools ensure that firms can effectively implement agile strategies in practice, aligning with customer needs and market dynamics in real time (Magistretti and Trabucchi 2024). This study focuses on the perspective of adopting agile management tools that together enable organizations to respond effectively to dynamic environments.

The current discussion on antecedent variables of organizational agility focuses on three key dimensions: technical, organizational, and environmental. The technological dimension includes IT capabilities (Deng et al. 2021; Aral and Weill 2007; Gao et al. 2020; Mao et al. 2023), digital technologies (Côrte-Real et al. 2017; Ravichandran 2018; Vial 2019; Saputra et al. 2022), data enablement (Qi et al. 2021; Stylos et al. 2021), and other factors; the organizational level includes organizational behavior (Bouguerra et al. 2021; Ferraris et al. 2022), organizational culture (Carvalho et al. 2019), leadership styles (Aurélio de Oliveira et al. 2012; Abbas and Ali 2023), and digital transformation leadership (AlNuaimi et al. 2022); the environmental dimension includes factors such as environmental volatility (Tallon and Pinsonneault 2011), environmental dynamics (Lee et al. 2015), and environmental uncertainty (Ahammad et al. 2021; Darvishmotevali et al. 2020). Digitalization is to some extent a mix of technical and environmental dimensions. While the technical and environmental dimensions are overarching categories, digitalization is a more granular element underneath both. Digitalization helps firms achieve rapid data collection, real-time decision-making and flexible resource allocation through the adoption and integration of digital tools, platforms and technologies (Adomako and Nguyen 2024; Tallon et al. 2019). At the same time, digitalization reflects the characteristics of the modern business environment. Companies operating in the evolving environment of the digital economy must engage with and adapt to this reality (Lu et al. 2024; Qi et al. 2021).

While previous studies have explored the correlation between organizational agility and variables in the dimensions of technology, organization, and environment, there is still a lack of in-depth exploration of the causes of organizational agility during sudden public events, especially in the context of the booming digitalization era. The sudden public events (such as pandemics, natural disasters, etc.) have posed significant challenges to firms’ operations and development. However, the impact of digitalization, as one of the important tools to address these challenges, on organizational agility has not been fully explored. Therefore, conducting in-depth research on the influence of digitalization on organizational agility in the context of sudden public events can enrich existing research and provide more effective strategies and decision-making support for firms facing future emergencies.

Resource-based theory

When facing changes in the external environment, firms need to fully utilize internal resources to quickly adapt to changes, flexibly respond to challenges, and gain competitive advantages. The resource-based theory provides a theoretical framework that can help understand the importance and impact of digital resources on organizational agility. Resource-based theory (RBT) posits that a firm’s unique bundle of resources and capabilities can be a source of sustained competitive advantage (Barney 1991; Freeman et al. 2021). Wernerfelt (1984) provided a definition of resources in the 1980s, stating that they include all assets that can either benefit or harm an organization. These assets comprise both tangible and intangible elements, such as capital, specialized and technical workers, as well as knowledge and experience. However, in the current era of digitalization, data has become a new factor of production (Ritter and Pedersen 2020). Mechanism innovation, propelled by digitalization, can expedite the dissolution of data impediments and information disparity. This, in turn, empowers corporations to seamlessly amalgamate the requisite internal resources for business operations. Furthermore, it imbues them with the agility necessary to nimbly adapt to fluctuations in market demand (Ravichandran 2018).

Through reviewing relevant research, it has been found that the digital resource foundation plays an important role in the formation of organizational agility (Tallon et al. 2019). In particular, the resource base becomes even more crucial for fostering organizational agility amidst crisis situations (Al-Omoush et al. 2020; Nijssen and Paauwe 2012). Consequently, resource-based theory is highly applicable for investigating the process by which organizational agility is developed in the setting of unexpected public events. In such scenarios, both internal and external environments undergo sudden transformations, and the evolution of organizational agility exhibits pronounced shifts in power dynamics and dynamism. This necessitates organizations to swiftly acclimate to external environmental changes via resource amalgamation and capability configuration. Hence, this study intends to delve into the influence of the digitalization on organizational agility within the context of unexpected public events, drawing upon the resource-based theory.

Dynamic capability theory

In the context of digitalization and organizational agility, relying solely on static resource advantages is no longer sufficient to address the swift changes in the market. It is in this backdrop that the dynamic capabilities theory emerges, representing a further extension and deepening of the resource-based view. Dynamic capability is the ability of a firm to construct, integrate and reconfigure its internal and external resources to manage the swift changes in the business environment (Teece et al. 1997; Eisenhardt and Martin 2000). The theory explains how firms can adapt to the rapidly changing external environment and gain competitive advantages. It has garnered considerable scholarly interest since its inception, particularly in the era of the digital economy where its theoretical significance is increasingly prominent (Helfat and Raubitschek 2018). The theoretical hypothesis states that firms that possess strong dynamic capacities are better equipped to navigate complicated and volatile market conditions (Teece et al. 1997). In practice, however, applying the digital experience that companies have acquired, either directly or indirectly, into their daily operations is challenging in reality (Niemand et al. 2021). This difficulty arises from various factors, including differences in organizational culture (Carvalho et al. 2019), the development stage of the firm (Tan et al. 2015), and the digital literacy of their employees (Cetindamar Kozanoglu and Abedin 2020). Given this, organizational agility from the perspective of dynamic capabilities theory focuses more on the micro level, emphasizing the capability to perceive and adapt to changes in both the internal and external environment, belonging to a specific subset of dynamic capabilities (Nijssen and Paauwe 2012). Digitalization can enhance the ability of firms to perceive opportunities, acquire and reconfigure internal and external resources in a dynamic environment, enabling them to keenly recognize and address the dynamic and complex competitive environment (Elia et al. 2021; Pergelova et al. 2019). It follows that dynamic capabilities theory provides a theoretical basis for exploring the impact of digitalization on organizational agility.

Hypothesis development

Impacts of digitalization on organizational agility

The outbreak of COVID-19 signifies the occurrence of extraordinary transformations in the global market environment. In the face of these challenges, firms need to fully utilize their resources, enhance dynamic capabilities, and improve organizational agility and precision. As a result, digital transformation has become one of the best business approaches for survival and growth in a changing environment (Chen and Tian 2022). Leveraging digitalization to improve resource allocation efficiency and reduce transaction costs can increase the agility of firms to deal with exogenous shocks (Copestake et al. 2024; Kraus et al. 2022).

Firstly, digitalization enables firms to reimagine traditional business models by integrating digital technologies into processes, products, and services (Peng and Tao 2022). For example, digital platforms allow firms to offer personalized customer experiences, while digital machines optimize resource allocation (Kholopov et al. 2018). These capabilities allow firms to adapt their operations in innovative ways, aligning with the reconfiguration processes emphasized by dynamic capabilities theory (Helfat and Raubitschek 2018).

Secondly, through digitalization, firms gain access to advanced analytics and real-time data, enabling them to identify and exploit previously underutilized resources (Chouaibi et al. 2022; Zahoor et al. 2023). For instance, IoT-enabled devices can monitor asset performance and optimize their use, enhancing efficiency and agility (Adomako and Nguyen 2024). According to resource-based theory, this demonstrates how digitalization enhances resource orchestration to achieve a competitive edge (Elia et al. 2021).

Finally, digitalization fosters creativity by facilitating collaboration, automating routine tasks, and enabling experimentation (Meng and Wang 2023). For example, firms can rapidly prototype solutions or launch new services through cloud platforms(Liu et al. 2023). These innovations are central to dynamic capabilities, as they allow firms to seize opportunities and adapt resource allocations to meet evolving market demands (Helfat and Raubitschek 2018; Stylos et al. 2021).

Based on the above analysis, we suggest:

H1: Digitalization has a positive effect on organizational agility.

Moderating effects of platform

The integrated development of digital economy and real economy has promoted the birth of Internet platform (Acs et al. 2021). The platform economy derived from the development of platforms has become the main form of economic organization and market operation mode of the digital economy (Bertani et al. 2021; Kenney and Zysman 2020). Compared with the traditional market model, the network effect of platforms enables them to provide lower-threshold and relatively equal transaction services for more market subjects and facilitate the conclusion of transactions(Sutherland and Jarrahi 2018), especially for the long-tail customers who could not be reached in the past due to time and space constraints (Cenamor et al. 2019; Helfat and Raubitschek 2018). Using platforms as a vehicle and digital technology as a tool, firms can change their traditional production and business models (Karhu et al. 2018), facilitating the integration of factor resources, improving their ability to respond to unforeseen circumstances, and realising more flexible production and distribution processes(Panico and Cennamo 2022), thus providing a tool for greater agility. While excessive platform participation introduces challenges that potentially diminish organizational agility (Hoang et al. 2020).

From the perspective of transaction cost theory (Williamson and Ghani 2012), firms participating in multiple platforms face increasing coordination costs. Each platform demands specific adjustments to inventory, pricing, and promotional strategies, leading to resource dilution and inefficiencies (Belhadi et al. 2023). For instance, simultaneous participation in JD and Tmall may require firms to manage separate advertising campaigns, pricing strategies, and logistics, which can strain their operational capacities. This undermines the agility-enhancing benefits of digitalization by introducing rigidity into decision-making and execution (Lafuente et al. 2024). In addition, the platform economy emphasizes ecosystem dynamics, wherein platforms are not merely tools but environments with distinct rules, algorithms, and user behaviors (Acs 2023). Firms that operate on too many platforms may encounter conflicting ecosystem demands, such as divergent promotional timelines or varying delivery requirements, which complicate their operational strategies (Panico and Cennamo 2022). These conflicts inhibit the fluidity and responsiveness that underpin organizational agility. Simultaneously, the cost of managing multiple platform relationships—whether in terms of fees, promotional budgets, or operational adjustments—can escalate, ultimately outweighing the agility benefits enabled by digitalization (Williamson and Ghani 2012).

Based on the theoretical discussion above, we posit that the relationship between digitalization and organizational agility is moderated by the number of platforms in which the firm participates. Specifically, as the number of platforms increases, the agility-enhancing benefits of digitalization diminish. Therefore, we assume the following:

H2: The impact of digitalization on organizational agility is negatively moderated by platforms, specifically through the number of platforms participated in.

Moderating effects of competitiveness

The impact of industry competitiveness on organizational agility is a complex topic that involves several aspects, such as organizational resources (Davcik and Sharma 2016), market environment (Chen et al. 2021; Porter and van der Linde 1995) and strategic decisions (Belohlav 1993; Sedliačiková et al. 2021). According to the resource-based theory, a firm’s competitive advantage comes from its unique resources and capabilities. These resources and capabilities are acquired and developed by the firm over a long period of development and cannot easily be copied or replaced by other firms (Barney 1991; Kozlenkova et al. 2014).

Exposed to a variety of market challenges, firms with a strong competitive position have undergone continuous iterations to optimize their organizational structures for decision-making efficiency and operational coordination (Andrew et al. 2006; Henry 2007). Such firms rely on robust process systems that ensure consistency, efficiency, and scalability in operations. These systems are often built over years of trial and error, innovation, and benchmarking against industry best practices (Teece et al. 1997). Additionally, competitive firms accumulate resources—both tangible (e.g., capital, infrastructure) and intangible (e.g., brand equity, intellectual property, and organizational knowledge)—through strategic investments and careful management. These resources are acquired and enhanced over time, providing the firm with a foundation that is difficult for competitors to replicate (Helfat and Peteraf 2003; Kozlenkova et al. 2014). Thus, for firms with strong competitiveness in the industry, they usually already have a well-developed organizational structure, process system and resource base (Mikalef and Gupta 2021; Davies and Brady 2000; Meso and Smith 2000; Olszak et al. 2018), which collectively constitute a complex intelligence system of the firm (Yeoh and Popovič 2016). These firms have typically achieved a high degree of resource optimization and operational stability (H. Chen and Hsu 2010), which positions them to maintain agility through existing internal mechanisms. A single digital tool may have a relatively limited effect on the agility of these firms, as digital tools are only one part of the firm’s complex intelligence system rather than a transformative driver (Elia and Margherita 2018). Consequently, the marginal benefit of digitalization in fostering agility is reduced because the firm’s existing capabilities already align closely with its competitive needs (Hellemans et al. 2022).

In contrast, firms with lower competitiveness are often constrained by inadequate organizational structures, inefficient processes, and limited resources. These deficiencies hinder their ability to respond promptly to market shifts or customer demands (Barney 1991; Belohlav 1993; Davcik and Sharma 2016). For such firms, digitalization can serve as a leapfrog mechanism, enabling them to overcome structural weaknesses and resource constraints (AlNuaimi et al. 2022). By providing access to real-time market information and improving operational efficiency, digital tools can enhance the responsiveness, innovation capabilities, and agility of these firms (Straker and Wrigley 2016; Stylos et al. 2021). For example, small or resource-constrained firms may use digital platforms to reach previously inaccessible customer segments or streamline operations through automated processes. These tools can substitute for resource-heavy traditional approaches, thereby leveling the competitive playing field (Lin et al. 2020). Unlike highly competitive firms, these firms derive a disproportionate benefit from digitalization, as it addresses critical gaps in their ability to adapt to environmental changes.

Therefore, we posit that the relationship between digitalization and organizational agility is moderated by a firm’s industry competitiveness. Specifically, firms with lower industry competitiveness are more likely to experience a significant enhancement in agility through digitalization, whereas the effect is less pronounced for highly competitive firms with well-established systems already in place. Based on the above analysis, we believe that:

H3: The impact of digitalization on organizational agility is negatively moderated by industry competitiveness.

Methodology

Empirical setting and data

The data used in this article comes from the Enterprise Survey for Innovation and Entrepreneurship in China (ESIEC) led by Peking University. The survey aims to obtain micro-data reflecting the status of innovation and entrepreneurship of Chinese enterprises through scientific sampling and field tracking surveys (Dai et al. 2021). The baseline survey was conducted in 2018, using the industrial and commercial registration database as the sampling frame. The research team employed a probability sampling strategy proportional to firm size, selecting 117 counties across six provinces—Liaoning, Shanghai, Zhejiang, Henan, Guangdong, and Gansu (Cong et al. 2024). A total of 58,500 enterprises were sampled, and more than 900 trained student interviewers conducted in-person visits. In 2020, the ESIEC project team launched a special follow-up survey titled “The Survival Status of Small, Medium, and Micro Enterprises under COVID-19” to capture firms’ responses and resilience during the pandemic. In this survey, 8750 enterprises were contacted for follow-up, and 2519 valid responses were collected, yielding a follow-up response rate of 44.5%. This study leverages both waves of the survey to construct a balanced panel dataset. Specifically, we retain only those firms that successfully participated in both the 2018 and 2020 surveys. The key independent variables are measured using the 2020 follow-up data, while other variables are measured using the 2018 baseline data. After excluding firms with missing values in key variables across the two surveys, the final analytical sample consists of 1588 firms. This matched panel structure enables us to examine the predictive relationship between pre-crisis digitalization levels and organizational agility during the COVID-19 crisis, while ensuring consistency and robustness in the empirical analysis. This study categorized and summarized the industry distribution of the sampled firms. The results show that the sample covers a wide range of industries, with a relatively high proportion of firms in manufacturing (16.88%), wholesale and retail (14.80%), accommodation and catering (11.65%), leasing and business services (11.40%), and repair and other services (11.08%), indicating a high degree of industry diversity and representativeness. It is worth noting that the study includes platform participation and competitiveness as moderating variables. While firms may differ in their level of platform dependency or the intensity of market competition they face, these variables exhibit sufficient variation within the sample, providing a robust basis for analyzing the mechanisms through which digitalization affects organizational agility. The detailed industry distribution of the sample is presented in Table 1.

Table 1 Distribution of sample firms by industry.
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Variable definition

Dependent variable: organizational agility

Organizational agility refers to a firm’s ability to sense and respond effectively to environmental changes by adjusting business strategies, reconfiguring resources, and seeking innovative solutions (Doz 2020; Teece et al. 1997). This study operationalizes organizational agility as a dynamic capability that manifests through specific actions taken by firms in response to external shocks, such as the COVID-19 pandemic.

The definition of organizational agility unfolds in three dimensions. The first is the strategic dimension. This dimension reflects a firm’s ability to adjust its strategic direction in response to external disturbances. As emphasised by the dynamic capabilities theory, organizations need to dynamically sense and respond to environmental signals in order to remain aligned with market demands (Helfat and Peteraf 2003). The next dimension is the operational dimension. According to the resource base theory, the resources owned by a firm are heterogeneous, and the competitive advantage of a firm is rooted in its special resources. This requires fully exploring the unique resources owned by the enterprise and optimising the use of existing assets to ensure continuity (Kozlenkova et al. 2014). Finally, there is the innovation dimension. This dimension reflects the ability to implement creative solutions to new challenges. Resource-based theory emphasises the role of intangible assets, such as knowledge and the ability to innovate, which can help firms to seize opportunities in unexpected situations (Davcik and Sharma 2016).

To measure organizational agility, we utilize data from the May 2020 follow-up survey of ESIEC, specifically leveraging responses to three survey items that capture firms’ adaptive and innovative behaviors. Respondents were asked to indicate the extent to which their firm had undertaken the following actions since the onset of the pandemic:

  1. 1.

    Changing traditional business models and recombining resources,

  2. 2.

    Identifying underutilized resources and recombining them,

  3. 3.

    Seeking creative solutions and reallocating resources accordingly.

Respondents rated their agreement with each statement on a five-point Likert scale, ranging from 1 (“None”) to 5 (“Always”). The scores for these three items were summed to derive an organizational agility score, which reflects the degree to which firms demonstrated agility during the crisis.

Independent variable: digitalization

In line with prior research, this study conceptualizes digitalization as a firm’s use of digital technologies that facilitate information processing, coordination, and responsiveness across business activities (Alekseeva et al. 2021). Given the structure of the dataset, we measure digitalization using two observable dimensions: 1) Internet use, which captures digitalization in operational and market-facing activities, and 2) use of digital machines (e.g., industrial robots), which reflects digitalization in production processes. Internet use includes business activities such as marketing through social media, online sales on e-commerce platforms, and customer management through personal websites or apps (Bartelsman et al. 2018). The use of the Internet can reduce the cost of searching, copying, transporting, tracking, and verifying information (Goldfarb and Tucker 2019), which can help companies to reduce costs and increase efficiency in their operations. These practices are widespread among SMEs and represent the integration of digital tools into external and customer-related functions. In contrast, the use of digital machines reflects more advanced forms of digital adoption typically associated with manufacturing firms and automation. Though more sector-specific, this dimension captures firms that have begun digitizing core production workflows, thereby contributing to agility in supply chain reconfiguration and production flexibility. While these two components differ in application scenarios and technological intensity, they both embody firms’ efforts to integrate digital tools into core activities to improve coordination, efficiency, and adaptability. Given the diversity of industries in the sample, combining these two dimensions allows us to capture heterogeneous manifestations of digitalization. Accordingly, a firm is coded as 1 if it reports using either the internet or digital machines, and 0 otherwise.

Moderate variables: platform participation and competitiveness

Platform participation

Platform participation is conceptualized as the extent to which firms engage with digital sales platforms to distribute their products or services. Digital platforms, such as e-commerce websites and third-party marketplaces, enable firms to reach broader customer bases, streamline operations, and adapt quickly to market demands (Eisenmann et al. 2011; Parker et al. 2017). However, participation across multiple platforms may also introduce coordination challenges, governance dependencies, and operational rigidities (McIntyre and Srinivasan 2017).

In this study, platform participation is measured by the number of digital platforms a firm uses, based on responses to a survey item that lists major e-commerce platforms. While we acknowledge that reliance on a single dominant platform can also imply risk and loss of bargaining power, we hypothesize that higher multi-platform participation may dilute strategic focus, increase compliance burdens, and reduce firms’ ability to respond nimbly in turbulent environments. This interpretation aligns with prior studies that highlight how platform governance and multi-homing complexity can constrain entrepreneurial autonomy (McIntyre and Srinivasan 2017). Accordingly, we test whether firms participating in a greater number of platforms experience a weake positive effect of digitalization on agility due to potential overextension and platform lock-in effects.

Competitiveness

Competitiveness refers to a firm’s relative ability to outperform industry peers in terms of operational and financial performance (Porter 1985). It captures a firm’s capacity to leverage its resources and capabilities to achieve superior market positioning. Higher competitiveness is often associated with greater organizational confidence and the ability to maintain strategic autonomy, which can influence the effectiveness of digitalization efforts on agility (Barney 1991).

To measure competitiveness, the study utilizes a perceptual survey item that asked respondents to evaluate the likelihood that their firm’s revenue growth between 2016 and 2017 exceeded the average growth of similarly sized firms in the same industry and region. Responses were recorded on a five-point Likert scale, ranging from 1 (“Absolutely impossible”) to 5 (“Definitely”). While we acknowledge that this indicator is perception-based and backward-looking, it captures managers’ self-assessed relative market performance, which is used in prior organizational behavior and strategic management studies where objective benchmarking is unavailable (Dess and Robinson 1984). We interpret this measure as a proxy for firms’ internal confidence and self-perceived competitiveness—factors that can meaningfully shape strategic behavior, including how firms leverage digital technologies to improve agility.

Control variables

To account for confounding factors that may influence the relationship between digitalization and organizational agility, this study incorporates control variables at both the firm level and the owner level. These variables are selected based on prior research (de Diego Ruiz et al. 2023; Doz 2020) and their relevance to organizational behavior and strategic decision-making.

Firm-Level control variables

Type of registration: The legal registration type of the firm (e.g., state-owned, private, joint venture) captures differences in regulatory environments, resource access, and strategic flexibility.

Firm age: Measured as the number of years since the firm’s establishment, firm age reflects organizational maturity and experience, which may influence agility.

Number of employees: Used as a proxy for firm size, this variable controls for the potential impact of organizational scale on agility, as larger firms may face greater inertia in adapting to changes.

Owner-level control variables

Owner age: Reflects the experience and generational perspective of decision-makers, which can influence strategic agility.

Owner gender: Gender diversity in leadership has been linked to variations in risk-taking and innovative behaviors, factors relevant to agility.

Owner educational level: Higher education levels are associated with greater managerial skills, analytical capabilities, and openness to change, all of which may shape a firm’s response to digitalization.

In addition, city fixed effects and industry fixed effects were added to the model. Table 2 offers the definitions of all the variables used in this study. Following that, Table 3 exhibits the descriptive statistics, and Table 4 shows the correlations between variables.

Table 2 Variable definitions.
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Table 3 Descriptive statistics.
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Table 4 Correlation matrix.
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Empirical method

To estimate the relationship between digitalization and organizational agility, this study employs an ordinary least squares (OLS) regression framework. The dependent variable, Agility, is measured using a perceptual survey item and is treated as an ordinal variable. While OLS is not ideal for ordinal data, it remains a widely used method in management and organizational research when the dependent variable exhibits sufficient variance and is reasonably continuous in interpretation. The key independent variable, Digitalization, is a binary indicator reflecting whether the firm adopts either Internet-based tools or digital production technologies. The baseline model is specified as follows:

$$Agilit{y}_{i}={\beta }_{0}+{\beta }_{1}Digitalizatio{n}_{i}+B^{\prime} X+\varepsilon$$
(1)

Where X is a column vector of control variables, including variables for firm’s registration types, age, number of employees, owners’ age, gender, and education level, as well as city fixed and industry fixed; and B is a column vector of the coefficients.

Then, in order to investigate whether the moderator variables Platform participation and Competitiveness have moderating roles in the effect of the independent variable Digitalization on the dependent variable Agility, this paper constructs corresponding moderating effect models for analysis. The models are as follows:

$$\begin{array}{lll}Agilit{y}_{i}&=&{\beta }_{0}+{\beta }_{1}Digitalizatio{n}_{i}+{\beta }_{2}Platfor{m}_{i}\\&& +\, {\beta }_{3}Digitalizatio{n}_{i}\times Platfor{m}_{i}+B^{\prime} X+\varepsilon\end{array}$$
(2)
$$\begin{array}{lll}Agilit{y}_{i}&=&{\beta }_{0}+{\beta }_{1}Digitalizatio{n}_{i}+{\beta }_{2}Competitivenes{s}_{i}\\&& +\,{\beta }_{3}Digitalizatio{n}_{i}\times \,Competitivenes{s}_{i}+B^{\prime} X+\varepsilon \end{array}$$
(3)

Results

Main results

Table 5 presents the results of the regression analyses that examine the relationship between digitalization and organizational agility, as well as the moderating effects of platform participation and firm competitiveness. Column (1) shows the regression results, including only the core explanatory variable, where it can be observed that the regression coefficient for digitalization is significantly positive (F = 5.505, p < 0.01), suggesting that digitalized firms exhibit higher levels of organizational agility compared to non-digitalized ones. Column (2) shows the regression results after including control variables, indicating that digitalization significantly enhances organizational agility (F = 5.679, p < 0.01), confirming the robustness of the effect. This means that, on average, firms adopting either internet-based tools or digital production technologies demonstrate an ~5.68-point increase in agility scores (on the underlying scale), compared to non-digitalized firms. This result supports H1, highlighting the positive impact of digitalization on agility. Column (3) exhibits overall good performance (F = 5.746, p < 0.01). The coefficient of interaction between digitalization and the number of platform is significantly negative (β = −5.894, p < 0.01), suggesting that the number of platforms negatively moderates the relationship between digitalization and organizational agility, in support of H2. This finding can be interpreted through the lens of platform governance theory and resource dependency theory. Specifically, while participation in digital platforms offers market access and visibility, multi-platform engagement may introduce governance complexity, heterogeneous operational standards, and increased reliance on external platform rules and algorithms (McIntyre and Srinivasan 2017). These constraints may limit the firm’s ability to autonomously reconfigure its operations and strategies, thereby reducing the flexibility that digitalization is otherwise expected to provide. In this sense, excessive platform dependence can transform digital tools from enablers of agility into potential sources of rigidity and external control, particularly for resource-constrained small and medium-sized enterprises (SMEs). Column (4) achieves statistical significance (F = 9.323, p < 0.01). The coefficient for the interaction term between digitalization and firm competitiveness is negative and significant (β = −0.054, p < 0.1), offering tentative support for H3. This result suggests that firms that perceive themselves as highly competitive derive less marginal benefit from digitalization in terms of agility gains. One theoretical explanation is rooted in behavioral strategy and organizational inertia literature: firms with strong competitive positioning may be more inclined to rely on established routines and successful legacy strategies, thereby exhibiting greater resistance to change and lower receptiveness to digitalization (Gilbert 2005; Hannan and Freeman 1984). In such firms, digitalization may be implemented in a symbolic or incremental manner, lacking the urgency or flexibility found in less dominant firms that must adapt more proactively to survive. Thus, competitiveness may function as a psychological buffer, reducing the strategic motivation to fully leverage digital technologies for agile transformation. Finally, the analysis of control variables reveals several significant effects consistent with existing theory. Firm size, proxied by the number of employees, is negatively associated with agility, supporting the idea that larger organizations face more bureaucratic inertia and structural rigidity. Conversely, owner education level exhibits a positive and statistically significant effect, suggesting that better-educated leaders may be more open to change, better equipped to implement digital technologies, and more proactive in driving adaptive strategies. Other variables, such as owner age and gender, show weaker or insignificant effects in this sample.

Table 5 Results of the main effect regression analyses.
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Addressing the endogeneity problem

Propensity score matching method

In order to overcome the endogeneity caused by systematic differences between samples that have been digitized and those that have not, this article uses propensity score matching (PSM) method for testing. Set the digitized enterprise as the processing group with a value of 1, and set the remaining groups as the control group with a value of 0. Secondly, using all control variables as matching covariates, nearest neighbor matching is used as the treatment group to find the only control group with the closest propensity score, which is used as the matching object for the former. Finally, the PSM matched treatment group and control group were empirically tested. The difference check before and after PSM matching is shown in Table 6. The p-values of the majority of variables before and after matching have changed from significant to insignificant, and the absolute value of the t-value after matching has significantly decreased, indicating a good matching effect. Finally, the matching results were input into the model for regression analysis. Column (1) of Table 7 reports the regression results of the PSM matched samples, which are consistent with the hypothesis testing results mentioned earlier. Therefore, after considering possible endogeneity issues, the previous research conclusions remain robust.

Table 6 Difference checking before and after PSM matching.
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Table 7 Results of the endogeneity test and robustness check.
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Heckman two-stage sample selection method

Considering the endogeneity issues that may arise from sample selection errors, this article employs the Heckman two-stage method for further testing (Heckman 1979). In the first stage of Probit estimation, the presence of agile behavior in the enterprise is taken as the dependent variable. If it exists, Agility_d is assigned a value of 1, otherwise it is assigned a value of 0. And use the geographical distance between the province where the firm is located and Hangzhou as the instrumental variable, while keeping the other control variables consistent with those in model (1). Calculate the inverse Mills ratio (IMR). Then, the IMR obtained in the first stage regression was used as an additional control variable and re-regressed in the second stage model, as shown in column (2) of Table 7. After controlling for sample selection bias, the coefficient of Digitalization remained significantly positive, consistent with the baseline regression results. The Heckman two-stage method test results indicate that the conclusion of this article is robust.

Robustness check

Replacement of independent variable

Digitalization often acts as an enabler of innovation. Innovation behavior often reflects the tangible outcomes of a firm’s digitalization efforts, such as the application of digital tools to create new value or improve efficiency. By tracking innovation activities, we capture the active implementation of digital capabilities in real-world organizational contexts, making it a suitable stand-in for digitalization. Drawing on the research (Lin et al. 2024), this study re-estimates the baseline regression using the firm innovation behavior as a proxy variable for digitalization. The regression results presented in Columns (3) of Table 7 show consistency with our main analysis.

Replacement of dependent variable

Organizational agility is fundamentally about the ability to react quickly to adapt and survive under uncertain or challenging conditions. The ability of a firm to remain operational during a period of significant disruption (e.g., the COVID-19 pandemic in 2020) serves as a proxy for agility, as it reflects the organization’s capacity to quickly adapt its operations, resources, and strategies to external shocks (de Diego Ruiz et al. 2023). This substitution aligns with the theoretical definition of agility because operational continuity during crises often requires rapid decision-making, flexibility, and innovation—key characteristics of agile organizations. We further use operations as an alternative measure of organizational agility to test the robustness of the regression. The results shown in Columns (4) (Table 7) are consistent with our main analysis.

Discussion

Using data from Enterprise Survey for Innovation and Entrepreneurship in China (ESIEC), we conducted an empirical analysis of Chinese micro, small and medium-sized enterprises (MSMEs), examining the impact of digitalization on organizational agility and the moderating role of platform participation and competitiveness therein. We drew on dynamic capabilities theory and resource-based theory to hypothesize the effect. The results suggest that digitalization will significantly enhance the agility of firms, helping them to be more flexible in adapting their business models to cope with a crisis. It is worth noting that the scale of this impact varies across platform participation and competitiveness, with firms that participate in fewer platforms and those that are less competitive in the industry benefiting more. Therefore, these findings contribute to the literature on digitalization and organizational agility, while also offering valuable practical guidance for enterprises.

Theoretical contributions

Our research contributes to the literature in four aspects. Firstly, it fills the theoretical gap in the relationship between digitalization and organizational agility. The existing academic comprehension of how digitalization affects organizational agility is not yet sufficient (Deng et al. 2021; Aral and Weill 2007; Haider and Kayani 2020; Cegarra-Navarro and Martelo-Landroguez 2020). Through systematic theoretical construction and empirical analysis, this paper reveals how digitalization can serve as a key driving force to promote the organizational agility. This discovery enhances the understanding of how to improve agility and provides a new perspective for the study of organizational agility. Additionally, our work also expands the research on the impact of digitalization, providing a solid theoretical foundation for the research in this field, and helping to promote the cross-integration of digitalization with organizational behavior, strategic management and other fields.

Secondly, we construct a more comprehensive and nuanced analytical framework of how digitalization affects firm agility by taking into account differences in the number of digital platforms involved, as well as individual differences due to the strengths and weaknesses of firm competitiveness. In previous studies, differences in the number of digital platforms involved and differences in the competitiveness of firms have not been sufficiently emphasized in previous studies, which has led to limitations (Lin et al. 2020; Tran 2021; Kwak et al. 2019). As we have seen, digital platforms and firm competitiveness serve as crucial moderators in the relationship between digitalization and firm agility, thus extending the understanding of the process shaping organizational agility.

Finally, the study reinforces the application of empirical research in examining the process of digitalization and the agile behavior of firms. In recent years, scholars have recognized the importance of digitalization in promoting agile behavior inside firms (Li et al. 2018; Niemand et al. 2021; Ritter and Pedersen 2020). However, most of the research is still confined to conceptual discussion and case discussion (Qi et al. 2021; Stylos et al. 2021). Empirical studies, on the other hand, focus more on listed companies. By adopting a large-sample empirical research method and focusing on micro and small enterprises, this paper not only verifies the applicability of existing theories, but also provides a more comprehensive perspective on the role of digitalization in enterprises.

Managerial implications

Our research is equally valuable to organizations in terms of management. First, it provides a decision-making basis for firms to formulate digital strategies. The wave of digital economy is unstoppable, and the crisis attribute attached to public emergencies such as COVID-19 has cast a cloud on the firm operation. Digital strategy has become a necessary path for enterprise transformation (Li et al. 2018). But there are just too many digital tools, and there is a certain amount of trial and error costs. The question of which approach should be adopted for digital upgrading, and what kind of digital means can truly help firms solve problems rather than being superficial, is a concern for firms. Our findings suggest that digitalization can improve organizational agility in the face of constantly changing market environments. Firms should review their resource distribution and allocate more resources to digital channels than others. We encourage firms to continuously invest in digital transformation, enhance organizational agility, and strengthen their innovative capabilities and market competitiveness. This will enable them to better respond to market changes and seize new business opportunities.

Second, our findings provide some practical guidelines for firms to flexibly handle their relationship with platforms. The study indicates that while digitalization positively contributes to organizational agility, an excessive number of platform engagements may dilute this benefit. Organizations should prioritize quality over quantity when engaging with Internet platforms. Instead of pursuing a broad presence across multiple platforms, firms should carefully evaluate and select platforms that align with their operational goals, customer base, and core competencies. A focused approach can help optimize resource allocation and enhance the agility benefits of digitalization. And we also emphasize to firms the importance of maintaining a sufficient level of independence and creativity. This will enable them to effectively adapt and respond to changes in platform strategies or market conditions, thereby minimizing the adverse effects of relying too much on platforms.

Third, our findings also prompt firms to review and reassess their competitiveness, make reasonable use of digitalization or seek alternative management approaches. For firms with strong competitiveness, although digitalization can bring them a certain degree of convenience and efficiency improvement, they may not fundamentally change their core competitiveness and operational models (Chen and Hsu 2010). Such firms still need to deeply analyze their core business and capabilities, actively explore strategies that meet their development needs, and organically combine them with digitalization and other means to ensure they stay ahead of the game in the ever-changing business environment. For firms with weak competitiveness in the industry, digitalization may become the key to breaking through and enhancing their competitiveness. These firms usually lack sufficient resources and experience to cope with the rapid changes in the market, and digitalization offers them a new and efficient mode of operation (Straker and Wrigley 2016). Such firms should accelerate digitalization layout, fully leverage their advantages, and assist themselves in quickly acquiring market information, optimizing operational processes, and enhancing innovative capabilities, thereby better adapting to market changes.

However, we cannot ignore the risks that digitalization may brings (Ciborra 2006; Sjöberg 2002). While digitalization offers benefits in terms of efficiency and convenience, it can also result in firms excessively depending on technology and disregarding the complexity of human factors and market changes (Uddin et al. 2023). Furthermore, the management and maintenance of digitalization necessitate a substantial allocation of resources and investment. Firms lacking adequate strength and resources may have greater risks (Liu et al. 2023). Therefore, when facing digital transformation, firms need to comprehensively assess their internal resources and capabilities, market environment, and long-term development strategies to formulate the most suitable digital strategy for themselves. Only then can a firm maintain a sustainable competitive advantage in an ever-changing market.

Limitations and future directions

Several limitations should be considered when interpreting the results. Firstly, while we adopt a functional perspective to capture both customer-facing and production-side digital tools, the combined use of internet-based technologies and digital machines may mask important distinctions between firms with different technological orientations. While the use of a binary independent variable simplifies interpretation,this approach inherently limits the ability to capture the diverse pathways and varying intensities of digital adoption across firms. We acknowledge this as a limitation of the current dataset and model design. Due to data constraints, we are unable to disaggregate their effects. Given this, future research could benefit from more fine-grained measurement strategies that differentiate between various types and intensities of digital technology use. Multi-dimensional indices or continuous variables may better reflect the depth and scope of digitalization and offer insights into how specific configurations of digital tools influence organizational agility. Furthermore, future studies could explore sector-specific effects or conduct industry-stratified analyses to more precisely identify the role of digitalization in shaping agility outcomes across different operational contexts.

Secondly, the study lacks direct performance indicators, such as revenue growth or market share, to assess the concrete outcomes of digitalization and agility during crisis periods. Future research could prioritize longitudinal data collection or integrate financial metrics to evaluate how agile responses enabled by digitalization translate into tangible competitive advantages. Such an effort would provide stronger empirical evidence for the strategic value of digital transformation.

In addition, while this study focuses on organizational agility in crisis situations, particularly those involving sudden public events like the COVID-19 pandemic, it does not encompass all possible types of crises. Future research could broaden this scope by examining the impact of digitalization on organizational agility across a variety of crisis scenarios, including economic recessions, industry-specific disruptions, or geopolitical crises. This would allow for a more comprehensive understanding of the contingencies under which digitalization fosters agility.

Finally, although the moderating role of digital platform participation is discussed, the study does not differentiate between specific types of platforms. Future research could extend this work by investigating the unique impacts of various platform types, such as transactional platforms versus innovation-oriented platforms, and exploring their interaction with firm-specific capabilities and external market dynamics. This would offer a more detailed understanding of the mechanisms through which digital platforms enhance organizational agility.