Promoting the Sustainable Development of Organizations: Technological Capability, Environmental Uncertainty, and Enterprise Exploratory Innovation

Abstract

Exploratory innovation plays a crucial role in the high-quality and sustainable development of organizations, but how enterprises engage in exploratory innovation within volatility, uncertainty, complexity, and ambiguity (VUCA) contexts remains unclear. Drawing on strategy choice theory and continuous innovation theory, this study explores the positive effects of technological capability on exploratory innovation via entrepreneurial orientation while considering environmental uncertainty as a moderating variable to elucidate the internal logic of continuous innovation within organizations. We conducted a large-scale survey of 313 Chinese firms and found the following: (1) technological capability has a significant positive impact on exploratory innovation; (2) entrepreneurial orientation plays a partial mediating role between technological capability and exploratory innovation; and (3) environmental uncertainty exerts a differential moderating influence within this mediating framework: technological uncertainty enhances the positive effect of technological capability on entrepreneurial orientation, whereas demand uncertainty intensifies the supportive effect of entrepreneurial orientation on exploratory innovation. This study reveals the internal mechanism by which technological capabilities drive exploratory innovation through entrepreneurial orientation under environmental uncertainty, providing theoretical support for enterprises to deepen their technological capability and pursue exploratory innovation and sustainable development.

1. Introduction

The contemporary business environment in China is undergoing substantial changes, characterized by extreme volatility, uncertainty, complexity, and ambiguity (VUCA). In this unpredictable environment, firms encounter unparalleled challenges to survival and growth, requiring significant and continuous adaptive adjustments [1]. One of the most effective strategic adaptations to such turbulent contexts is innovation, which provides a sustainable source of competitive advantage for enterprises [2]. In particular, exploratory innovation, which involves generating and acquiring new knowledge, enables enterprises to detect early signals of change, reconfigure resources effectively, enhance their dynamic adaptability [3], and respond flexibly to unexpected events. Furthermore, exploratory innovation enhances organizational resilience by cultivating a learning-oriented culture that supports recovery, renewal, and even growth following disruptions [4]. Exploratory innovation has thus emerged as a crucial method for enterprises to navigate the VUCA environment and attain high-quality and sustainable development. Exploratory innovation is a comprehensive and fundamental innovation endeavor that enables enterprises to intricately integrate knowledge innovation with technological innovation, revolutionize organizational technology paradigms, and achieve original technological breakthroughs. Enterprises seek fundamental technological breakthroughs through exploratory innovation, which can overcome the dilemma of technological homogenization, establish unique market and technological positions [5], and achieve sustainable development. However, not all enterprises’ exploratory innovations yield positive innovation performance. Judging from the current exploratory innovation practices of enterprises, neglecting the intricate contexts they encounter and blindly pursuing exploratory innovation may result in diminished innovation efficiency, the erosion of core competitive advantages, and falling into the “trap” of innovation [6]. Consequently, how enterprises should cope with the challenges posed by complex environments and implement exploratory innovation under significant environmental uncertainty has become a critical issue that requires urgent resolution.

To address the influence of complicated contexts on exploratory innovation, it is essential to delineate the primary situational aspects that impact this innovation. Strategic choice theory indicates that enterprises operate within an open system, interacting with and impacting the surrounding environment. Situational perspective and contingency thinking are important premises for relevant theoretical research [7]. Existing research has summarized the determinants of enterprise exploratory innovation from the vantage point of both the internal and external circumstances of enterprises. From the viewpoint of an enterprise’s internal circumstances, technological capabilities represent the experiential knowledge and heterogeneous resource integration accumulated by enterprises in continuous innovation [8], which is an important internal factor affecting exploratory innovation. Studies have shown that enterprises with strong technological capabilities are more inclined to actively address path dependence and other significant challenges. This approach has been proven to have a positive effect on exploratory innovation and promote sustainable enterprise growth [9,10,11]. In addition to technological capabilities, the propensity of enterprises to actively innovate, i.e., their entrepreneurial orientation, is another important internal factor affecting the strategic choice of enterprise exploratory innovation [12]. Entrepreneurship involves the accumulation of competitive advantages via exploratory innovation, with entrepreneurial orientation playing a crucial role in driving enterprise exploratory innovation activities [13]. The external circumstances of an organization, including its sociocultural and institutional context, also play a critical role in shaping its trajectory and adoption of innovation and sustainable development. Recent research highlights that the adoption and impact of technologies are deeply embedded in the political and institutional contexts within which firms operate. For example, Stratu-Strelet et al. (2023) reported that in developing Latin American countries, the efficacy of information and communication technologies in driving sustainable development depends heavily on institutional conditions such as democratic governance, citizen participation, and institutional trust [14]. These findings suggest that technological capabilities alone may not be sufficient to drive innovation unless supported by enabling sociopolitical environments. Therefore, understanding the mechanisms by which technological capabilities drive exploratory innovation should also consider environmental factors. Continuous innovation theory posits that technical and market environmental uncertainties are the paramount external situational elements influencing sustainable innovation in organizations and determine the scope and intensity of innovation activities carried out by enterprises [15]. The intricate system of internal and external factors constitutes a complex situational framework that significantly influences enterprises’ exploratory innovation [16].

Although these insights have improved our understanding of exploratory innovation, they often fail to consider the interactive effects of internal and external situational factors on enterprises’ exploratory innovation. Most current studies look at technological capabilities, entrepreneurial orientation, or environmental uncertainty separately, without considering how both internal and external factors work together to influence exploratory innovation [16]. Second, prior studies have frequently conceptualized environmental uncertainty in an excessively simplistic manner. In the context of the digital economy, however, the widespread use of digital technologies, platforms, and infrastructures profoundly reshapes both innovation processes and the conditions under which innovation occurs [17]. Recent research indicates that digital transformation markedly improves organizations’ exploratory innovation by facilitating information absorption [18], fostering dynamic capability growth [19], and enhancing the focus on digital innovation [20]. In this context, the interaction between firms’ technological capabilities and external environmental uncertainties—particularly technological and market uncertainty—has become a critical foundation for understanding exploratory innovation [21]. Third, there is a lack of theoretical frameworks examining the influence of technology and the market on organizations’ sustainable innovation from the perspective of long-term development.

To bridge these gaps and enrich our understanding of how technological capability affects enterprise exploratory innovation, this study formulates a comprehensive analytical framework of resource foundation–strategic orientation–strategic behavior grounded in strategic choice theory and continuous innovation theory. Taking into account a firm’s internal technological and external environmental conditions, we systematically examine the influence of technological capabilities on exploratory innovation through entrepreneurial orientation while addressing the dual aspects of environmental uncertainty (technological and demand uncertainty).

The framework of this study is as follows: Section 2 constructs the theoretical framework and proposes research hypotheses; Section 3 introduces the methodology of this study; Section 4 presents the results of the empirical analysis; and Section 5 discusses the research findings, theoretical significance, and practical implications and highlights the limitations and future directions.

2. Theoretical Framework and Hypotheses

2.1. Technological Capabilities and Exploratory Innovation

Existing research presents diverse perspectives on the concept of technological capabilities, including resource-based and knowledge-based views. The resource view holds that technological capabilities are the integration of different types of resources accumulated by enterprises, such as relevant technology experience, tacit knowledge, and skills [8], including technological knowledge, technological connections, and technological innovation practices [22], which is an important channel through which enterprises establish core competitive advantages [23]. The knowledge view is a refinement and derivation of the resource view, believing that technological capabilities are the ability of enterprises to identify, absorb, integrate, apply, transform, and create new technological knowledge [24]. Technological capabilities can be regarded as a collection of tangible and intangible knowledge of enterprise technologies. This study comprehensively defines such resource and knowledge views, assuming that technological capabilities belong to the category of capabilities, referring to the heterogeneous knowledge resource integration that enterprises identify, absorb, integrate, apply, and transform and the creation of new technological knowledge, and reflecting the judgment, mastery ability, and innovation potential of enterprises in terms of technological trends.

Exploratory innovation refers to the innovation model in which enterprises move beyond existing technologies, products, and services; break the shackles of existing knowledge [16]; and crossover to new technological tracks. The results of exploratory innovation are more disruptive, enabling enterprises to seize market opportunities and gain excess profits [3], so its significance lies in helping enterprises actively adapt to environmental changes, especially discontinuous and turbulent environmental changes [23]. Exploratory innovation is an important path for continuous innovation in enterprises [25]. However, this innovation model generally requires a large amount of resource investment and is accompanied by a greater risk of failure, which has greater requirements for enterprises’ technological capabilities. The current literature suggests that a company’s capacity to assess and implement new technologies in product innovation is a significant antecedent variable driving enterprise exploratory innovation [16,26]. Research indicates that constraints on the original technological trajectory and the inability to foresee and identify emerging technology prospects significantly impede enterprise exploratory innovation [23]. In summary, enterprises need to seek new possibilities through exploratory innovation and carry out more aggressive innovation activities to seize market opportunities [26]; they also need to have certain capabilities to cope with obstacles and challenges in exploratory innovation.

Continuous innovation theory posits that to achieve exploratory innovation in complex and uncertain contexts, organizations must have strategic foresight and adaptable learning mechanisms to respond consistently to changes in knowledge, customer needs, and external circumstances [27]. Strategic choice theory perceives organizations as proactive entities that may influence and adapt to their environments through intentional strategic decisions, rather than as passive responses to environmental changes [7]. Through deliberate strategic decisions, companies dynamically allocate internal and external resources and capabilities in response to changing market and technology circumstances. This strategic orientation facilitates the development of organizational learning practices and resource reconfiguration capabilities [28], both of which are crucial for sustaining innovation over time. Thus, strategic decision-making and strategic orientation, as emphasized by strategic choice theory, serve as the foundational mechanism through which firms shape organizational capabilities and enable continuous innovation. In VUCA environments, firms leverage internal resources and abilities via strategic decisions to pursue innovation-oriented pathways, hence promoting organizational adaptability and sustainable innovation [29].

Therefore, we argue that technological capabilities positively affect exploratory innovation. First, enterprises with strong technological capabilities possess a deep level of professional technological knowledge and accumulate sufficient explicit and tacit resources, both experientially and procedurally, during their technology development process. This enables them to quickly identify new technological tracks, experiment with emerging designs, and engage in product innovation that transcends current technological boundaries, thereby achieving exploratory innovation. Second, with the support of digital tools, enterprises with strong technological capabilities pay more attention to absorbing multisource and heterogeneous technological knowledge, ensuring the breadth of technological knowledge. Lin and Lai (2021) highlighted that in the fast-changing market of the digital economy, companies with strong technological capabilities gather many different types of technological knowledge, and new ideas for innovative projects often come from combining knowledge from various fields [23]. Third, in the digital context, enterprises with strong technological capabilities have diverse technological knowledge search channels, technology networks, and other technology-related complementary asset support, which can quickly involve external heterogeneous resources, accelerate resource flow, provide new possibilities, and open new ideas for enterprises to overcome technological problems and eliminate inertial thinking. Enterprises with strong technological capabilities can complete self-renewal and strengthening [24], cope with complex technological problems in exploratory innovation, stably play a role in technological activities, and ensure the smooth progress of exploratory innovation. Therefore, enterprises with high technological capabilities have sufficient technological resource stock and flow to form the complex resource basis required for exploratory innovation. Thus, this study proposes the following hypothesis:

H1. 

Technological capabilities are positively related to exploratory innovation.

2.2. The Mediating Role of Entrepreneurial Orientation

Entrepreneurial orientation is a portrayal and measurement of an enterprise’s entrepreneurial tendencies, willingness, and other mental models and management attitudes at the organizational level [30,31,32]. The essence of entrepreneurial orientation has been summarized as “a strategic orientation, decision-making style and behavior pattern” [33], “innovation strategy,” “entrepreneurial thinking or tendency” [31], and a “mental model” [34]. It is the internal driving force for enterprises to adopt entrepreneurial behaviors, discover entrepreneurial opportunities, and proactively pursue innovative activities [31]. Multidimensional constructivism explores the conceptual connotations of entrepreneurial orientation from the three dimensions of innovativeness, risk-taking, and proactiveness [30] and the five dimensions of innovativeness, risk-taking, proactiveness, competitive aggressiveness, and autonomy [35], emphasizing the importance of risk-taking and proactiveness in entrepreneurial orientation. This study suggests that entrepreneurial orientation is essentially a strategic position and decision-making tendency at the enterprise level, reflecting the three dimensions of innovativeness, risk-taking, and proactiveness in an enterprise’s strategic choice.

Technological capabilities originate from an enterprise’s R&D and manufacturing activities, reflecting its ability to acquire technological resources, carry out technological development, and form technological advantages [24]. Entrepreneurial orientation originates from an organization’s strategic choice after the internal and external environments are assessed and is essentially a strategic behavioral tendency [34]. The resource-based view and dynamic capabilities view suggest that an organization’s strategic tendency is dynamic. The resources and capabilities of a company can foster a strong entrepreneurial orientation, thereby boosting its exploratory innovation through the proactive pursuit of innovative activities and establishing a sustainable competitive advantage [34].

Therefore, technological capabilities can influence an enterprise’s entrepreneurial orientation for the following reasons. First, enterprises with strong technological capabilities are more willing to engage in innovation behaviors related to new products and technologies, thereby enhancing the innovativeness dimension of entrepreneurial orientation. Research has confirmed that enterprises with strong technological capabilities have unique resources conducive to technological innovation, such as talent, knowledge, organizational structure, and processes [22], thereby creating an organizational context and behavioral inertia favorable to knowledge integration, absorption, and utilization [36]. This implies that firms with significant technical competencies exhibit stronger knowledge management capabilities and are adept at transforming technical resources into corporate innovation, hence providing essential support for exploratory innovation [23]. Thus, enterprises with strong technological capabilities have higher levels of innovativeness.

Second, enterprises with strong technological capabilities have greater innovation proactiveness. Enterprises adopt advanced technologies to acquire and integrate strategic information, enhance their strategic planning abilities, and consequently boost their innovative initiative [37]. For example, Shi et al. (2022) confirmed that enterprises with strong technological capabilities have strong technological judgment and can quickly identify new technological opportunities in a turbulent environment, obtain high-value opportunity information [38], and thus are more willing to proactively pursue forward-looking innovation before competitors, shape the future environment, and open new niche markets to exclusively enjoy the results and high returns of innovation, demonstrating strong innovation proactiveness.

Furthermore, enterprises with strong technological capabilities reduce the riskiness and uncertainty of technological R&D; improve the efficiency and effectiveness of resource allocation; and thus improve the success rate of innovation, resulting in greater risk-taking [39]. For example, Lau and Lo (2019) show that enterprises with strong technological capabilities have stronger absorptive and transformative capabilities and can accurately judge their technological direction [40], thereby enhancing their risk-taking and increasing their support tendency for novel projects [31]. In summary, enterprises with strong technological capabilities demonstrate greater innovativeness, risk-taking, and proactiveness. Therefore, this study proposes the following hypothesis:

H2a. 

Technological capabilities are positively related to entrepreneurial orientation.

The accumulation of competitive advantage through exploratory innovation is an important aspect of entrepreneurship, and entrepreneurial orientation plays an important role in exploratory innovation activities [16]. From the standpoint of internal resource allocation, when a company embraces an entrepreneurial orientation grounded in heterogeneous technological resources to create new opportunities and vigorously engage in innovative actions, it will allocate resources prioritizing breakthrough and disruptive innovation activities, informed by risk-taking and innovation proactiveness [41], thereby enhancing the company’s exploratory innovation. On the other hand, enterprises with a strong entrepreneurial orientation have stronger strategic sensitivity to exploratory innovation. Enterprises with strong entrepreneurial orientation are highly sensitive to market changes [42] and pay more attention to innovation novelty and market responsiveness, which strategically buffers the market bottleneck after the transformation of exploratory innovation results and accelerates the exploratory innovation production process. Therefore, enterprises with a strong entrepreneurial orientation are more likely to form organizational practices and strategic insights conducive to exploratory innovation.

In addition, with respect to the three dimensions of entrepreneurial orientation, first, enterprises with strong innovativeness are more inclined to carry out exploratory innovation. Enterprises with strong innovativeness are more willing to pursue Schumpeterian innovation, constantly explore new knowledge, develop new opportunities [34], and seek novel and forward-looking technologies. Second, enterprises with strong risk-taking tendencies are more likely to accept a greater risk of exploratory innovation. Enterprises with strong risk-taking tendencies are willing to examine the enormous opportunities behind risks from a long-term perspective, make commitments, and take action for possible breakthrough results [31]; thus, they are more willing to try exploratory innovation, meet consumers’ demand preferences, and shape competitive advantages. Third, enterprises with strong proactiveness are more sensitive to opportunities for exploratory innovation and are more likely to take the lead in exploratory innovation. The proactiveness dimension of entrepreneurial orientation reflects an enterprise’s strategic posture of proactive competition, emphasizing the foresight of enterprise behavior and aggressiveness when facing competitors, indicating that enterprises learn quickly and try to establish new game rules. Therefore, enterprises with strong proactiveness are more likely to engage in exploratory innovation [16]. Therefore, this study proposes the following hypothesis:

H2b. 

Entrepreneurial orientation has a positive effect on exploratory innovation.

According to the resource-based view and strategic choice theory, a firm’s technological capabilities improve its knowledge management, risk identification, and strategic planning, thereby fostering innovation, innovativeness, and risk-taking. Hence, enterprises with heterogeneous technological resources have a strong entrepreneurial orientation, which prompts them to actively pursue innovative activities and allocate resources toward breakthrough and disruptive innovations, thereby enhancing exploratory innovation. In summary, enterprises with strong technological capabilities demonstrate a significant entrepreneurial orientation and are more likely to engage in exploratory innovation. Therefore, this study proposes the following hypothesis:

H2. 

Entrepreneurial orientation plays a mediating role between technological capabilities and exploratory innovation.

2.3. The Moderating Role of Environmental Uncertainty

Environmental uncertainty refers to a state in which the external environment that affects an enterprise’s survival frequently changes and is difficult to predict. Among these, technological and market uncertainties are the most important and direct situations at the enterprise level [43]. This study defines environmental uncertainty in two dimensions: technical and market uncertainty [15]. Among these, demand uncertainty is the main dimension of market uncertainty [44]. The external circumstances of an organization play a critical role in shaping the trajectory and adoption of its innovation and sustainable development. Recent research highlights that the adoption and impact of technologies are deeply embedded in the political and institutional contexts within which firms operate [14]. Prior studies have appropriately documented that environmental uncertainties may have an impact on innovation generation processes [45,46]. For example, Jean et al. (2018) [45] found that technological and market uncertainty moderate the link between strategic orientation and radical innovation. The continuous innovation perspective posits that sustainable innovation is inherent in an enterprise’s distinctive technology resources. The absorption, transformation, and invention of technology have been shown to enhance core competitiveness in firms functioning within a framework of independence and autonomy [27]. This has been demonstrated to improve the self-regulation of organizations during crises. Thus, this process is deemed essential for continual innovation in organizations, serving as a foundation for fostering organizational resilience and sustaining long-term competitive advantages. The increasing technological complexity of products gives rise to greater demand for innovation, which relies on organizational competencies in technology development and knowledge integration [47]. Market demand is a crucial factor in fostering sustainable innovation, and demand uncertainty enhances competitive intensity among firms, stimulates technological rivalry, and compels enterprises to innovate and enhance their product market share [46]. Greater market demand attracts the concentration of labor, technology, resources, and other innovative variables while also generating economies of scale to increase productivity. Increased market demand enhances the appeal of labor, technology, resources, and other inventive elements, thereby augmenting the technological innovation capacity of firms and subsequently advancing the organization’s sustainable innovation [48].

The main characteristic of technical uncertainty is that industry technologies change frequently, and multiple technological paradigms coexist, making it difficult for enterprises to judge the dominant technological direction [49]. The technological evolution perspective states that the evolution of a technological system alternates between linear evolution within paradigms and nonlinear evolution between paradigms [50]. When the technological system of an industry transitions between generations, a chaotic state of competition among multiple technological paradigms will appear, manifested as a technically uncertain environment. In the current context of the digital economy, various digital technologies, platforms, and infrastructures coexist, and the industry is undergoing frequent updates [17]. Technology lifecycle theory points out that the technical uncertainty environment is precisely the decline period of the old technological paradigm and the germination period of the new technological paradigm, incubating the birth of disruptive technologies in the “window of opportunity” [51]. Combining the basic viewpoint of strategic choice theory, we can conclude that technical uncertainty, as an important external situation, directly affects an enterprise’s innovation strategy choice. Research shows that when technical uncertainty is low, enterprises have less difficulty obtaining competitive information and are more inclined to implement differentiated competitive strategies through service innovation, model innovation, and other means [50,52]. In other words, when technical uncertainty is low, the uniqueness of technological capabilities in building an enterprise’s competitive advantage and other enterprises’ core competitive advantages are no longer significant. That is, the influence of technological capabilities on an enterprise’s strategic choice and strategic tendency is weakened.

Thus, we argue that when technical uncertainty is low, the positive effects of technological capabilities on entrepreneurial orientation and exploratory innovation weaken. When technical uncertainty is high, the positive effect of technological capabilities on entrepreneurial orientation and exploratory innovation is amplified. This is because, first, when technical uncertainty is high, enterprises with strong technological capabilities have a stronger entrepreneurial orientation. Frequent changes in industry technology send an important signal of “innovate or die” to enterprises [49], and enterprises must focus on innovative resource allocation to adapt to the turbulent environment. Enterprises with strong technological capabilities have stronger technology prediction capabilities and tend to adopt proactive strategies, resulting in greater organizational proactiveness [53]. Technical uncertainty leads to increased difficulty in industry innovation, and enterprises with strong technological capabilities have relatively higher innovation success rates and greater risk-taking willingness, strengthening their organizational entrepreneurial orientation. Second, when technical uncertainty is high, enterprises with strong technological capabilities are more inclined to engage in exploratory innovation. This is because when technical uncertainty is high, enterprises with strong technological capabilities have mastered more high-value technology information [54], and the scarcity value of their technological capabilities is more prominent. At this time, driven by the pursuit of excess returns from technological innovation, enterprises have a stronger motivation to proactively carry out fundamental and exploratory innovation, try to take the lead in achieving technological track leaps, formulate favorable industry technology standards and rules [55], master technological discourse power, and enjoy Schumpeterian innovation rent. Having comprehensively analyzed the above, this study proposes the following hypotheses:

H3. 

Technical uncertainty positively moderates the relationship between technological capabilities and entrepreneurial orientation.

H4. 

Technical uncertainty positively moderatesthe mediating role of entrepreneurial orientation between technological capabilities and exploratory innovation.

Demand uncertainty refers to a situation in which the market changes rapidly and enterprises have difficulty fully or accurately grasping customer demand information, making it difficult to predict market development trends [44]. As a direct environment for enterprise survival, demand uncertainty plays an important role in organizational strategy formulation and innovation model selection. When demand is relatively stable, an enterprise’s ability to search for and collect effective market information and its social capital become key sources of competitive advantage. Even enterprises with high technological capabilities will exhibit a propensity for conservative innovation under such conditions, prioritizing economies of scale to capitalize on emerging market opportunities and secure a dominant market position rather than engaging in high-risk exploratory innovation [56]. Enterprises with strong entrepreneurial orientation are also more inclined to realize competitive advantage acquisition through incremental innovation and other means and have low enthusiasm for exploratory innovation. Therefore, low demand uncertainty weakens the impacts of technological capabilities and entrepreneurial orientation on exploratory innovation. On the other hand, when demand uncertainty is high, enterprises with strong technological capabilities are inclined toward exploratory innovation. To achieve greater competitive advantages, enterprises cannot depend solely on their previous limited resource advantages to secure Ricardian rent. Enterprises with strong technological capabilities, possessing more technological resources and discourse power, tend to “take a different path” and have a stronger willingness for exploratory innovation [16], attempting to seek fundamental technological changes to break through market dilemmas and maintain market position.

On the other hand, enterprises with a strong entrepreneurial orientation are more likely to carry out exploratory innovation. Enterprises with a strong entrepreneurial orientation often have a greater willingness to take risks and adopt exploratory innovation, driven by significant survival pressure and the desire to reshape the future competitive landscape [8]. Simultaneously, enterprises with a strong entrepreneurial orientation are more alert and sensitive to technological innovation opportunities. They are no longer satisfied with simple product upgrades and iterations but seek to proactively carry out exploratory innovation to gain first-mover advantages, lead the direction of market development, seize market opportunities, and shape the future competitive landscape [13]; therefore, demand uncertainty amplifies the positive effect of technological capabilities and entrepreneurial orientation on exploratory innovation [46]. Having comprehensively analyzed the above, this study proposes the following hypotheses:

H5. 

Demand uncertainty positively moderates the relationship between entrepreneurial orientation and exploratory innovation.

H6. 

Demand uncertainty positively moderatesthe mediating role of entrepreneurial orientation between technological capabilities and exploratory innovation.

The conceptual model of this study is shown in Figure 1.

3. Methodology

3.1. Design and Sample

The sample data for this study were drawn from enterprises in Qinhuai Silicon Valley, Nanjing, Jiangsu Province, China, a regional innovation ecosystem with a strong focus on technology and innovation, aligning closely with the objectives of the research. Given this study’s focus on organization-level relationships, senior executives were chosen as the survey objects. To improve the accuracy of the survey, the research team initially conducted in-depth interviews with executives of five representative enterprises in Qinhuai Silicon Valley, including Jincheng Group Co. (Nanjing, China), and refined several items in the questionnaire based on their feedback. The research team subsequently organized an enterprise service symposium in Qinhuai Silicon Valley, with overall coordination provided by the person in charge of the Qinhuai Silicon Valley. During the symposium, the research team presented the primary findings of the study to representatives of each enterprise. They also provided a comprehensive explanation of the questionnaire survey and encouraged enterprises to participate actively by completing it.

A total of 583 questionnaires were distributed to executives of Qinhuai Silicon Valley enterprises, and 545 questionnaires were ultimately retrieved, yielding a recovery rate of 93.5%. Following the elimination of questionnaires that exhibited obvious abnormalities or missing data, 438 valid questionnaires were obtained, yielding a valid questionnaire recovery rate of 75.13%. The sample includes firms of different sizes, industries, and ownership types; the specific characteristics of the sample are presented in

Table 1. The demographic characteristics of the sample and the statistical characteristics of the enterprises.

Characteristics	Category	Percentage	Characteristics	Category	Percentage
gender	female	48.2%	industry classification	high-tech industry	66.9%
	male	51.8%		non-high-tech industry	33.1%
education	technical college or less	19.2%	enterprise ownership	state-owned enterprise	41.6%
	bachelor’s degree	66.2%		private enterprise	54.3%
	master’s degree or above	14.6%		other	4.1%
age	20–30 years old	35.8%	firm size	below 100 people	58.2%
	31–40 years old	43.8%		100–300 people	28.8%
	41–50 years old	15.1%		300–500 people	3.9%
	above 50 years old	5.3%		above 500 people	9.1%

.

3.2. Measures

To ensure the reliability and validity of the measurement tool, this study employed a widely recognized maturity scale published in authoritative domestic and international journals. Since the survey was conducted in China, we strictly followed the established translation/back-translation procedure to adapt the original English scales to Mandarin Chinese. All survey items were evaluated on a 5-point Likert-type scale (1 = strongly disagree and 5 = strongly agree).

Table 2. Measurement items and validity assessment.

Variables	Items	Factor Loading	Cronbach’s α	CR	AVE
Technological capabilities	Compared to major competitors, my firm masters state-of-the-art technologies	0.718	0.923	0.759	0.512
	Compared to major competitors, my firm is constantly developing a series of innovations	0.724
	Compared to major competitors, my firm possesses technology that is difficult to imitate	0.704
Entrepreneurial orientation	My firm has marketed very many new lines of products or services since its establishment	0.676	0.946	0.905	0.577
	Changes in product or service lines have usually been quite dramatic since the establishment of my firm	0.745
	In general, the top managers of my firm favor a strong emphasis on R&D, technological leadership, and innovation	0.806
	In general, the top managers of my firm have a strong proclivity for high-risk projects (with chances of very high returns)	0.729
	When confronted with decision-making situations involving uncertainty, my firm typically adopts a bold, aggressive posture in order to maximize the probability of exploiting potential opportunities	0.710
	In dealing with its competitors, my firm is very often the first business to introduce new products/services, administrative techniques, operating technologies, etc.	0.795
	In general, the top managers of my firm believe that owing to the nature of the environment, bold, wide-ranging acts are necessary to achieve the firm’s objectives	0.838
Exploratory innovation	Our company often pioneers entirely new market segments in which we have no prior marketing experience	0.762	0.908	0.823	0.537
	Our company often adopts business strategies or technologies that have not been used by other firms in our industry	0.75
	Our company regularly employs new technologies or skills that are immature and involve some risk	0.715
	Our company consistently develops breakthrough products or services that represent fundamental innovations	0.704
Technical uncertainty	The technology in this industry is changing rapidly	0.783	0.913	0.888	0.666
	Technological changes provide substantial opportunities in this industry	0.777
	A large number of new product ideas have been made possible through technological breakthroughs in this industry	0.863
	It is very difficult to forecast where the technology in this area will be in the next few years	0.838
Demand uncertainty	The market demand in this industry is growing rapidly	0.795	0.861	0.770	0.529
	Customers are consistently in pursuit of novel products	0.719
	Customers who have never bought our products may also develop a demand for them	0.662

presents the reliability and validity of the variables.

Technological capabilities. Technological capabilities were measured via the scale adopted by Zhou and Wu [26]. This scale consists of three items: technological sophistication, the speed of acquiring new technologies, and the difficulty in imitating technology. All the items are presented in Table 2.

Entrepreneurial orientation. We measured entrepreneurial orientation via the scale developed by Hu and Zhang [57]. This scale includes three dimensions (innovativeness, risk-taking, and proactiveness) and seven items. All the items are presented in Table 2.

Exploratory innovation. We measured exploratory innovation via a 4-item scale adapted from Fu, Li, and Si [58]. All the items are presented in Table 2.

Environmental uncertainty. We measured environmental uncertainty via a scale developed by Jaworski and Kohli [59]. The scale comprises seven items, four of which are intended to measure technical uncertainty and three of which are selected to measure demand uncertainty. All the items are presented in Table 2.

Control variables. We controlled for several sociodemographic variables to mitigate the potential biases resulting from individual and organizational differences. The control variables included gender (1 = male, 2 = female), age (1 = 20–30 years, ..., 4 = above 50 years), and educational level (1 = technical college or less, ..., 3 = master’s degree or above). Organizational attributes such as enterprise ownership (1 = state-owned enterprise, ..., 3 = other), enterprise size (1 = less than 100 people, ..., 4 = more than 500 people), and industry classification (1 = high-tech industry, 2 = non-high-tech industry) were also considered.

3.3. Preliminary Analyses

3.3.1. Reliability and Validity of Constructs

We refined the measures and assessed their reliability and validity as follows. First, we assessed the reliability of each focal construct via Cronbach’s α and composite reliability (CR). As shown in Table 2, Cronbach’s α for all the constructs exceeded 0.80, indicating high internal consistency reliability. Similarly, the CR values for all the constructs exceeded 0.70, meeting the recommended threshold and further supporting the reliability of the measures.

Furthermore, we performed exploratory factor analysis (EFA) to establish construct validity. The analysis yielded excellent factorability (KMO = 0.953; Bartlett’s χ² = 8831.638; p < 0.001). As shown in Table 2, all the items exhibited strong factor loadings above 0.65 on their intended theoretical dimensions, with no notable cross-loadings. Additionally, the average variance extracted (AVE) for each construct exceeded the recommended threshold of 0.50, providing solid evidence of convergent validity. Collectively, these findings demonstrate the measurement instrument’s strong construct validity.

To rigorously assess discriminant validity among the focal constructs, we performed confirmatory factor analysis (CFA) via Mplus 7.0. As shown in

Table 3. Confirmatory factor analysis of construct combinations.

Model	χ2	df	χ2/df	RMSEA	SRMR	CFI	TLI
TC, EO, ERI, TU, DU	737.331	196	3.76	0.079	0.044	0.942	0.931
TC, EO, ERI, TU+DU	902.610	200	4.51	0.090	0.054	0.924	0.912
TC, EO+ERI, TU+DU	1336.914	203	6.59	0.113	0.062	0.878	0.861
TC+EO+ERI, TU+DU	1626.580	205	7.93	0.126	0.065	0.847	0.827
TC+EO+ERI+TU+DU	2606.548	206	12.65	0.163	0.093	0.741	0.710

Note: TC/EO/ERI/TU/DU represent technological capabilities, entrepreneurial orientation, exploratory innovation, technical uncertainty, and demand uncertainty, respectively.

, the hypothesized five-factor model demonstrated a superior fit (χ²/df = 3.76, CFI = 0.942, TLI = 0.931, RMSEA = 0.079, SRMR = 0.044) compared with alternative models, providing strong evidence of discriminant validity.

3.3.2. Common Method Bias

The latent common method factor approach was employed to assess the potential for common method bias. As demonstrated in

Table 4. Common method bias test.

Model	χ2/df	RMSEA	SRMR	CFI	TLI
Original model	3.76	0.079	0.044	0.942	0.931
Single-factor model incorporating a common latent factor	2.90	0.066	0.028	0.964	0.953
Change in model fit indices	−0.86	−0.013	−0.016	0.022	0.022

, the incorporation of a common method factor into our baseline measurement model resulted in negligible enhancements in model fit, and the alterations in comparative fit indices (CFI and TLI) were below the 0.01 threshold, whereas adjustments in RMSEA and SRMR remained within 0.05. These results suggest that common method bias is unlikely to pose a substantial problem in this study.

4. Results

4.1. Descriptive Statistics

As shown in

Table 5. Descriptive statistics.

Variable	N	Mean	SD	Min	Max	Skewness	Kurtosis
Technological capabilities	438	3.61	0.81	1.00	5.00	0.18	−0.64
Entrepreneurial orientation	438	3.60	0.77	1.14	5.00	0.17	−0.29
Exploratory innovation	438	3.50	0.90	1.25	5.00	0.27	−0.76
Technical uncertainty	438	3.96	0.72	2.00	5.00	−0.19	−0.71
Demand uncertainty	438	3.81	0.71	2.00	5.00	0.05	−0.73
Gender	438	0.52	0.50	0.00	1.00	−0.07	−2.00
Age	438	1.90	0.84	1.00	4.00	0.73	−0.04
Education	438	1.96	0.59	1.00	4.00	0.07	0.17
Ownership	438	1.63	0.59	1.00	4.00	0.59	0.88
Industry	438	1.67	0.47	1.00	2.00	−0.72	−1.49
Firm size	438	1.63	0.92	1.00	4.00	1.51	1.35

, the descriptive statistics of the main variables are reported, including the sample size, means, standard deviations, minimum, maximum, skewness, and kurtosis, which help assess the distributional characteristics of the data. The skewness and kurtosis tests reveal that the absolute values of skewness and kurtosis for all model variables are below 2 (with gender exhibiting a kurtosis value of −2.00), falling within the optimal range (±2), thereby indicating that the data’s normality is acceptable and fulfills the criteria for linear regression analysis.

Table 6. Correlation matrix of main variables.

Variable	1	2	3	4	5	6	7	8	9	10	11
1 TC	1
2 EO	0.423 ***	1
3 ERI	0.509 ***	0.410 ***	1
4 TU	0.301 ***	0.255 ***	0.269 ***	1
5 DU	0.383 ***	0.266 ***	0.342 ***	0.343 ***	1
6 Gender	−0.05	−0.082	−0.090	−0.067	−0.083	1
7 Age	−0.124 **	−0.041	−0.109 *	0.035	−0.079	0.268 **	1
8 Education	−0.150 **	−0.113 *	−0.193 **	−0.004	−0.043	0.116 *	0.098 *	1
9 Ownership	0.086	0.066	0.083	−0.048	−0.048	−0.085	−0.130 **	−0.186 **	1
10 Industry	−0.045	−0.050	−0.019	0.047	0.044	−0.125 **	−0.017	−0.179 **	−0.016	1
11 Firm size	−0.162 **	−0.113 *	−0.102 *	0.083	0.067	0.033	0.256 **	0.213 **	−0.522 **	0.045	1

Note: TC/EO/ERI/TU/DU represent technological capabilities, entrepreneurial orientation, exploratory innovation, technical uncertainty, and demand uncertainty, respectively; * indicates a significance level of p < 0.05, ** indicates a significance level of p < 0.01, and *** indicates a significance level of p < 0.001 (two-tailed test).

presents the correlation analysis among the main variables. The results reveal that technological capabilities are positively correlated with entrepreneurial orientation, exploratory innovation, technical uncertainty, and demand uncertainty; that technical uncertainty is positively correlated with entrepreneurial orientation and exploratory innovation; that demand uncertainty is positively correlated with entrepreneurial orientation and exploratory innovation; and that entrepreneurial orientation is positively correlated with exploratory innovation. The correlation between the variables preliminarily verified the research hypotheses proposed in this study.

Given that the observed correlation coefficients ranged from low to moderate, additional diagnostic tests were conducted to assess potential multicollinearity issues. The variance inflation factors (VIFs) for all variables were well below the conventional threshold of 10 (ranging from 1.064 to 2.513), with the corresponding tolerances all exceeding 0.1, effectively alleviating multicollinearity concerns.

4.2. Hypothesis Testing

4.2.1. Main Effect and Mediating Effect Testing

Hierarchical regressions were initially conducted to examine the relationship between technological capabilities and exploratory innovation, followed by employing the bootstrapping method with the PROCESS plugin in SPSS 27.0 to test the mediated moderation effects [60]. The results of Model 2 in

Table 7. Regression analysis results.

Variable	Entrepreneurial Orientation		Exploratory Innovation
	M3	M4	M1	M2	M5	M6
Control variables
Gender	−0.078	−0.067 *	−0.054	−0.044	0.003	−0.017
Age	0.008	0.069 *	−0.070	−0.010	−0.076 *	−0.038
Education	−0.104 *	0.000	−0.184 ***	−0.084 *	−0.108 **	−0.084 **
Ownership	−0.005	0.004	0.020	0.029	0.024	0.027
Industry	−0.078	−0.026	−0.062	−0.012	−0.006	−0.002
Firm size	−0.090	−0.001	−0.030	0.056	0.035	0.056
Independent variable
Technological capabilities		0.770 ***		0.744 ***		0.437 ***
Mediating variable
Entrepreneurial orientation					0.729 ***	0.399 ***
F	2.178	89.125	4.115	84.237	80.375	96.605
R2	0.032 *	0.594 ***	0.055 ***	0.580 ***	0.569 ***	0.645 ***
ΔR2		0.562 ***		0.525 ***	0.514 ***	0.065 ***

Note: N = 438; * p < 0.05, ** p < 0.01, and *** p < 0.001 significance level (two-tailed test).

show that after controlling for demographic characteristics such as gender, age, and education level, as well as enterprise characteristics such as industry, nature, and size, technological capabilities have a significant positive effect on exploratory innovation (β = 0.744, p < 0.001). Therefore, Hypothesis 1 is supported by the data.

Model 4 in Table 7 shows that technological capabilities exert a positive and significant effect on entrepreneurial orientation (β = 0.770, p < 0.001). This result is in line with previous findings that enterprises with technological capabilities are likely to increase their entrepreneurial orientation [55], supporting Hypothesis 2a. Model 5’s results demonstrate that entrepreneurial orientation has a positive effect on exploratory innovation (β = 0.729, p < 0.001), supporting Hypothesis 2b. Model 6 indicates that, after the simultaneous addition of technological capabilities and entrepreneurial orientation, entrepreneurial orientation and exploratory innovation are significantly positively correlated (β = 0.399, p < 0.001), and the relationship between technological capabilities and exploratory innovation remains significant (β = 0.437, p < 0.001). These results show that entrepreneurial orientation partially mediates the relationship between technological capabilities and exploratory innovation. Furthermore, the bootstrap sampling results in

Table 8. Results of mediating effect.

Effect Type	Effect Value	Boot SE	Bootstrap 95%CI		Effect Proportion
			Lower Limit	Upper Limit
Total effect	0.748	0.032	0.683	0.811	100.00%
Direct effect	0.436	0.046	0.345	0.526	58.29%
Indirect effect	0.312	0.041	0.233	0.394	41.71%

show that technological capabilities have a significant indirect effect on exploratory innovation through entrepreneurial orientation (IE = 0.312, p < 0.05; CI [0.233, 0.394]). Therefore, Hypothesis 2 is supported by the data.

4.2.2. Moderating Effect Test of Technical Uncertainty

The results of Model 3 in

Table 9. Results of moderation effect.

Variable	Entrepreneurial Orientation			Exploratory Innovation
	M1	M2	M3	M4	M5	M6
Control variables
Gender	−0.067 *	−0.054	−0.050	0.003	0.005	0.014
Age	0.069 *	0.053	0.053	−0.076 *	−0.046	−0.037
Education	0.000	−0.013	−0.011	−0.108 **	−0.112 ***	−0.118 ***
Ownership	0.004	0.005	0.018	0.024	0.030	0.045
Industry	−0.026	−0.040	−0.035	−0.006	−0.025	−0.024
Firm size	−0.001	−0.030	−0.028	0.035	−0.011	−0.010
Independent variable
Technological capabilities	0.770 ***	0.646 ***	0.089
Mediating variable
Entrepreneurial orientation				0.729 ***	0.531 ***	−0.142
Moderating variable
Technical uncertainty		0.209 ***	−0.177
Demand uncertainty					0.312 ***	−0.227
TC×TU			0.838 **
EO×DU						1.098 ***
F	89.125	87.806	80.138	80.375	89.120	83.399
R2	0.594 ***	0.622 ***	0.629 ***	0.569 ***	0.626 ***	0.638 ***
ΔR2		0.028 ***	0.007 ***	0.514 ***	0.057 ***	0.012 ***

Note: N = 438; * p < 0.05, ** p < 0.01, and *** p < 0.001 significance level (two-tailed test).

show that the interaction term between technological capabilities and technical uncertainty has a positive and significant effect on entrepreneurial orientation (β = 0.838, p < 0.01), thus supporting Hypothesis 3. Furthermore, the interactive effect diagram in Figure 2a shows that when technical uncertainty is high (one SD above the mean), the positive relationship between technological capabilities and entrepreneurial orientation is stronger than when technical uncertainty is low (one SD below the mean). These findings support Hypothesis 3 asserting that when technical uncertainty is high, the effect of technological capabilities on entrepreneurial orientation is positively stronger.

To further explore the moderated mediating effect proposed in Hypothesis 4, the bootstrapping method in PROCESS was applied; the results are presented in

Table 10. Results of moderated mediation effect.

Path	Moderating Variable	Effect Value	Boot SE	Bootstrap 95%CI
				Lower Limit	Upper Limit
1: Technological capabilities → Entrepreneurial orientation → Exploratory innovation	Low technical uncertainty	0.504	0.063	0.380	0.629
	High technical uncertainty	0.696	0.041	0.614	0.777
	Difference between groups	0.192	−0.022	0.234	0.148
2: Technological capabilities → Entrepreneurial orientation → Exploratory innovation	Low demand uncertainty	0.267	0.059	0.152	0.382
	High demand uncertainty	0.438	0.051	0.339	0.537
	Difference between groups	0.171	−0.008	0.187	0.155

Note: Low technical uncertainty represents the mean minus 1 standard deviation; high technical uncertainty represents the mean plus 1 standard deviation; low demand uncertainty represents the mean minus 1 standard deviation; high demand uncertainty represents the mean plus 1 standard deviation.

. It can be seen from the results of Path 1 that the moderated mediation effect was 0.696 (95% CI = [0.233, 0.394]), in which the CI did not contain 0, suggesting that the moderated mediation effect was significant. The results indicate that the indirect effect of technological capabilities on exploratory innovation via entrepreneurial orientation is stronger when technical uncertainty is high (versus low), collectively supporting Hypothesis 4.

4.2.3. Moderating Effect Test of Demand Uncertainty

The results of Model 6 in Table 9 show that the interaction term between entrepreneurial orientation and demand uncertainty has a positive and significant effect on exploratory innovation (β = 1.098, p < 0.001), thus supporting Hypothesis 5. Furthermore, the interactive effect diagram in Figure 2b shows that when demand uncertainty is high (one SD above the mean), the positive relationship between entrepreneurial orientation and exploratory innovation is stronger than when demand uncertainty is low (one SD below the mean). These findings support Hypothesis 5 asserting that when demand uncertainty is high, the relationship between entrepreneurial orientation and exploratory innovation is positively stronger.

The results of Path 2 in Table 10 show that the indirect effect of technological capabilities on exploratory innovation via entrepreneurial orientation is stronger when demand uncertainty is high (vs. low). As shown in Table 10, the moderated mediation effect was 0.438 (95% CI = [0.339, 0.537]), and the CI did not contain 0, suggesting that the moderated mediation effect was significant. Therefore, Hypothesis 6 is supported by the data.

5. Discussion

This study focuses on the intricate internal and external contexts of corporate technological innovation and empirically examines the relationships among technological capabilities, entrepreneurial orientation, and exploratory innovation in Chinese enterprises, revealing a more complex moderating effect of environmental uncertainty than existing studies suggest.

The empirical findings demonstrate a significant positive relationship between technological capability and exploratory innovation, indicating that firms with stronger technological capabilities exhibit a greater propensity for exploratory innovation. This finding is inconsistent with Zhou and Wu’s (2010) inverted U hypothesis, which conceptualizes technological capability as organizational inertia that potentially constrains exploration beyond certain thresholds [26]. However, we emphasize the resource attributes of corporate technological capability, arguing that greater heterogeneity in a firm’s technological resources leads to stronger knowledge management and absorption capabilities. This prompts the firm to pursue higher-risk projects and drive exploratory innovation. As Ge and Liu (2022) highlight in their research, the synergy between internal technical capabilities and external knowledge absorption is critical for innovation performance [36]. This conclusion aligns with the research of Lavie et al. (2006), who emphasize that organizational slack and absorption capacity theories better explain function-based exploration in firms than organizational inertia theories do [5]. Thus, our findings demonstrate a sequential mechanism whereby technological capabilities foster entrepreneurial orientation, which, in turn, promotes exploratory innovation.

This study reveals that entrepreneurial orientation partially mediates the relationship between technological capability and exploratory innovation. The resource-based view suggests that firms with greater technological capabilities have greater technological capabilities and greater technological “resource position barriers” [8]. Strategic choice theory posits that firms make strategic decisions on the basis of subjective assessments of the external environment and internal resources [7]. Building on the above theory, this study explores how the evaluation of a firm’s technological resources shapes its strategic orientation and promotes exploratory innovation. The findings support previous discussions on how strategic orientation influences exploratory innovation through the corporate resource base. For example, Jean et al. (2018) [45] proposed a theoretical model of “strategic orientation–learning ability–innovation outcomes” in the context of supply chains and international enterprises. They argued that strategic orientation, such as long-term and customer orientation, can facilitate corporate innovation by improving joint learning ability [45]. Thus, our findings demonstrate a sequential mechanism whereby technological capabilities foster entrepreneurial orientation, which, in turn, promotes exploratory innovation.

Additionally, the results reveal the nuanced moderating role of environmental uncertainty in the relationship between technological capabilities and exploratory innovation. Specifically, technical uncertainty amplifies the positive effect of technological capabilities on entrepreneurial orientation and enhances EO’s mediating role of entrepreneurial orientation between technological capabilities and exploratory innovation. This finding is inconsistent with the view of Jeans et al. (2018), who proposed that technological uncertainty negatively moderates the impact of joint learning capabilities on breakthrough innovation [45]. A potential explanation for this inconsistency is that, amid technological uncertainty, exploratory innovation utilizing a company’s own technical expertise and resources is far less costly than breakthrough innovation attained through cross-organizational collaborative learning [49]. When technical uncertainty is low, businesses rely less on their technological skills, making it easier to find alternatives. This reduces the impact of these skills on their approach to entrepreneurship and innovation, such as collaborative learning. When technical uncertainty is high, the importance of technological capabilities to enterprises increases, and the irreplaceability of technological capabilities increases. In tough survival situations, enterprises with strong technological capabilities show greater entrepreneurial orientation [38] and are more likely to pursue exploratory innovation.

Demand uncertainty strengthens the influence of entrepreneurial orientation on exploratory innovation and enhances the mediating role of entrepreneurial orientation between technological capabilities and exploratory innovation. The findings indicate that the mediating effect of entrepreneurial orientation between technological capabilities and exploratory innovation is more significant when demand uncertainty is high than when demand uncertainty is low. When demand is stable and predictable, enterprises tend to be less innovative and focus more on improving existing products rather than on exploring new ideas; consequently, the influence of technological skills and the propensity for risk-taking in new innovations is reduced, leading rational enterprises to exhibit diminished entrepreneurial orientation [61]. However, when demand is unpredictable, enterprises usually become more open to new ideas. Those with strong technological capabilities tend to “take a different path” and seek fundamental technological changes to break through market dilemmas, and their willingness for exploratory innovation is stronger [16].

5.1. Implications

5.1.1. Theoretical Implications

First, this study enriches comprehensive contextual research on exploratory innovation. Single or fragmented contextual studies are limited in their ability to explain practical problems faced by enterprises. This study analyzes the VUCA context faced by enterprise exploratory innovation from three different dimensions, i.e., internal technological capabilities, entrepreneurial orientation, and environmental uncertainty, which overcomes the research limitations of previous studies that explored the impact of internal factors or external contexts on exploratory innovation separately and effectively enhances insights into the process of enterprise exploratory innovation.

Second, this study broadens the use of strategic choice and continuous innovation theories within the domain of exploratory innovation. By integrating strategic choice theory and continuous innovation theory in an environment characterized by volatility, uncertainty, complexity, and ambiguity, technological capabilities are seen as distinctive resources that are difficult for enterprises to imitate, whereas entrepreneurial orientation is considered a strategic orientation. Through the development of the theoretical framework of the resource base, strategic orientation, and strategic behavior, we elucidate the mechanism influencing exploratory innovation from the viewpoints of strategic choice theory and strategic entrepreneurship theory.

Finally, this study comprehensively examines the moderating effects of distinct elements of environmental uncertainty, specifically technical and demand uncertainty, on the relationship between firms’ technological capabilities and exploratory innovation. By deconstructing environmental uncertainty into different components from the technology and market dimensions, this study extends the boundary conditions between technological capabilities and exploratory innovation from an uncertainty perspective, providing a more nuanced understanding of the application of environmental uncertainty theory and challenging the previous monolithic treatment of environmental uncertainty in the literature.

5.1.2. Practical Implications

This study provides several managerial insights. First, it provides an important and realistic reference for enterprises to improve their technological capabilities and promote exploratory innovation. The data show that the R&D investment ratio of Chinese enterprises is far lower than that of enterprises in developed countries. Certain enterprises are constrained by “technological capability rigidity” and a “low-cost advantage”, leading to a reluctance to invest significantly in technology R&D, resulting in low technological capabilities and insufficient breakthroughs in exploratory innovation. This study indicates that, in the digital age, enterprises must enhance their exploratory innovation by expanding and deepening their technological knowledge through strategies such as establishing innovation networks and developing technological innovation practices. Such actions will expedite the generation of original, significant, and disruptive innovations and foster sustained innovation and growth. For example, compared with numerous established and renowned automobile manufacturers, BYD (Shenzhen, China), as an emerging entity, encounters frequent fluctuations in new energy vehicle technology standards and ambiguity regarding the industry’s future direction. BYD fosters technological advancements and industry leadership by enhancing investment in research and development, establishing an open innovation platform, establishing the BYD Technology Research Institute, and launching the Innovation Incentive Fund. These initiatives encourage business units to propose new projects at the grassroot level, promote internal entrepreneurship, and facilitate cross-border exploration, leading to continuous technological breakthroughs.

Second, enterprises can sustain entrepreneurial orientation through the accumulation of technological capabilities, which enhances the quality of innovation within the organization. Research findings indicate that enterprises exhibiting robust entrepreneurial orientation demonstrate increased enthusiasm for engaging in exploratory innovation. Enhancing entrepreneurial orientation in enterprises is directly linked to the advancement of innovation quality. This study demonstrates that enhancing technological capabilities significantly contributes to improving enterprise entrepreneurial orientation. Consequently, enterprises must prioritize the establishment of organizational practices and a cultural environment that enhances technological capabilities, emphasizes technological updates and self-optimization, and develops an organizational understanding of technological innovation. This approach enables enterprises to identify and seize potential opportunities within a volatile environment, enhance their proactive capabilities [61], improve their entrepreneurial orientation, and effectively foster exploratory innovation. For instance, Enel (Rome, Italy) has established the “Enel Innovation Centre” and the “Open Innovation Platform”. Through these centers, the company continuously accumulates technical experience and solicits hundreds of start-up teams and technical projects from around the world each year, thus maintaining a high level of innovation. In 2023, Enel collaborated with several technology companies to pilot AI-driven smart grid dispatching and distributed energy storage projects, thereby promoting the large-scale application of renewable energy.

Finally, enterprises should prioritize increasing technological investments, enhancing technological capabilities, and ensuring sustainable long-term development in complex environments characterized by high uncertainty. The research findings indicate that enterprises possessing robust technological capabilities experience more opportunities than challenges in environments characterized by high levels of uncertainty. In contexts characterized by high technological uncertainty, firms possessing robust technological capabilities are more inclined to implement proactive strategies, engage in exploratory innovation, capitalize on technological opportunities, and achieve “Schumpeterian innovation rent”. When technological indeterminacy is pronounced, leading firms, such as Huawei (Shenzhen, China), leverage robust technological resource networks to incorporate and integrate external emerging resources, thereby facilitating significant disruptive innovation. High demand uncertainty prompts enterprises with a robust entrepreneurial orientation to exhibit greater risk-taking propensity and engage in exploratory innovation to redefine their competitive advantages [8]. For example, in the domain of home appliances and smart manufacturing, confronted with rapidly changing market demands, Haier (Qingdao, China) has established a diversified portfolio encompassing refrigerators, smart homes, and the Internet of Things sector through its “people–order integration” platform-based organization and open incubation model, alongside its “maker lab” mechanism that empowers frontline employees to satisfy market needs and quickly integrate their technical skills, thereby fostering exploratory innovation in products and services.

5.2. Limitations and Future Research

While this study provides valuable insights, it has certain limitations that suggest directions for future research. First, this study primarily examines technical and demand uncertainty as key environmental factors. Nonetheless, it fails to account for competitive uncertainty, which refers to the unpredictability of rivals’ strategic actions and is particularly crucial in VUCA contexts. Although this focus ensures conceptual clarity, it may reduce the comprehensiveness of the analysis. Future research could include competitive uncertainty as an additional moderator to better capture the complexity of external influences on innovation behavior.

Second, the use of cross-sectional data restricts the analysis of long-term trends in firms’ technological capabilities that influence exploratory innovation. Future research could conduct an in-depth analysis of the long-term patterns of environmental uncertainty and the internal resources of firms that influence exploratory innovation by utilizing longitudinal study data.

Third, the research sample data were obtained from resident enterprises in Qinhuai Silicon Valley, Nanjing, China. Although these regional firms are representative of innovation and entrepreneurship, their observed behavior may be influenced by the local policy landscape and regional resource availability. Given that more than 60% of the sampled firms are science and technology start-ups, innovation patterns and research findings may only be relevant to the nascent stages of innovation. Consequently, subsequent research can enhance the generalizability of the findings by employing multiregional stratified sampling and incorporating samples from firms at various stages of their life cycle.

Finally, the advancement of digital technology has significantly expanded the breadth and depth of firms’ technological knowledge. Consequently, future research on firms’ technological capabilities may become increasingly intricate, allowing for a more thorough exploration of the contributions and impacts of digital technology integration capabilities.

6. Conclusions

Despite its limitations, this study is significant for comprehending the relationship between technological capabilities and exploratory innovation in intricate business environments. This study develops a dual moderating model to examine the impact of intrinsic business characteristics and external environmental uncertainty on firms’ exploratory innovation. The results indicate that technological capability positively affects enterprises’ exploratory innovation via the mediating role of entrepreneurial orientation, whereas environmental uncertainty can increase this effect. Technological uncertainty amplifies the influence of technological capabilities on entrepreneurial orientation, whereas demand uncertainty intensifies the effect of entrepreneurial orientation on exploratory innovation. These findings help clarify how a company’s technological abilities impact exploratory innovation, providing useful ideas and practical advice for businesses to handle exploratory innovation in complex contexts.