Digital transformation in small and medium-sized enterprises: key insights for entrepreneurs and policymakers to cultivate a future-ready business

Digital transformation has become a key focus in today’s swiftly moving global economy (Lee, Liu, Trappey, Mo, & Desouza, 2021). Similarly, it combines digital technology with effective corporate models to build great enterprise value (Lee et al., 2021). Digital transformation has attracted widespread attention to support “small and medium enterprises (SMEs)” to become more efficient and competitive in today’s rapidly growing business landscape. These innovations are shifting how enterprises work, live and interact (Hongyun et al., 2023). The intelligent utilization of digital innovation assists in protecting the environment, mitigating climate change and attaining Sustainable Development Goals (SDGs).

The SME sector has proactively responded to environmental uncertainties and changes by seizing financial prospects to evolve from the Internet to digital. According to the McKinsey Global Institute, firms can boost their efficiency by 20% if they embrace digital innovation (Hongyun et al., 2023). Despite the potential for significant benefits, SME institutions have been lagging in digital transformation (OECD, 2021). Therefore, digital transformation has attained significant attention in management research and practice to reshape business models and enhance operational efficiency across small enterprises.

This academic field is pioneering, intriguing and pivotal for several reasons. Firstly, Al Issa and Omar (2024) reported a tremendous increase in digital transformation investment across several industries. For instance, in 2018, approximately US$1.3 trillion was allocated to digital transformation. Despite the widespread attention to digital transformation, scholarly research has given surprisingly limited focus to these advancements (Hausberg, Liere-Netheler, Packmohr, Pakura, & Vogelsang, 2019; Verhoef et al., 2021). Thus, this article represents a fresh perspective to analyse the factors impacting the digital transformation of small firms. Second, the paper adds to the academic literature by recognizing Indian SMEs because, as a geographical setting, Srinivas (2022) reported that India will play a significant role in democracy by empowering digitally transformed institutions. Despite the expanding research on digital transformation, existing studies have predominantly emphasized developed nations, e.g. Switzerland (Mettler, Miscione, Jacobs, & Guenduez, 2024) and Taiwan (Tsai & Su, 2022). While some studies have explored developing nations, e.g. Indonesia (Aminullah et al., 2024) and China (Nureen, Sun, Irfan, Nuta, & Malik, 2023), they also warrant additional scholarly exploration on digital transformation in SMEs across other developing nations. Similarly, the NCR is identified as a major centre for information technology (IT) in the geographic landscape. Furthermore, this province hosts a varied and substantial SME population (Kumar, Rani, Rani, & Rani, 2024), reflecting the nation’s economic and cultural diversity. As a result, the findings are broadly generalizable and widely applicable to the broader business landscape. Considering this, our study makes an initial attempt to analyse the factors driving digital transformation from the viewpoint of an emerging nation such as India.

Third, organizational innovativeness is the ability of a corporation to implement new ideas, processes and business models that enhance efficiency, competitiveness and adaptability. An innovative culture promotes receptivity to novel concepts and enhances the capability to integrate innovation that supports service and product growth (Al Issa & Omar, 2024). Further, Aggarwal, Baker, and Joshi (2024) emphasize the requirement to examine novel insights and contribute to the ever-expanding knowledge of organizational innovation. Thus, this paper strives to fill the prevailing gap by investigating the factors affecting organizational innovativeness to foster a deeper understanding among small businesses. Fourth, the financial performance of an enterprise is vital to bring competitive advantages and enhance operational efficiency. Verhoef et al. (2021) emphasize a dearth of academic literature on how organizations facilitate digital transformation and their effect on performance. Furthermore, previous research has established links between digital transformation and bank performance (Abdurrahman, Gustomo, & Prasetio, 2024), innovation performance (Hongyun et al., 2023) and firm performance (Mai, Nguyen, Ton, & Ahmed, 2024). However, research examining the impact of digital transformation on financial performance remains scarce. Accordingly, this paper contributes to the prevailing literature by delivering new evidence on the relation between digital transformation and financial performance of small businesses in “India’s National Capital Region (NCR)” domain. Given these concerns, this paper strives to fulfil these concerns:

The article advances the prevailing literature and the existing scholarly discourse in several key areas. Firstly, we incorporated the well-established theoretical model, including the “resource-based view (RBV) theory, value co-creation (VCC) theory and processing efficiency theory (PET),” to measure how small enterprises can utilize their resources to enhance innovativeness and strengthen financial performance. Second, this paper enhances the existing academic discourse by answering the calls for additional studies from Hausberg et al. (2019) on the factors affecting digital transformation and Aggarwal et al. (2024) on organizational innovativeness that fuels technological innovation and promotes businesses’ long-term success and longevity. Accordingly, this work is among the initial efforts exploring the comprehensive impact of various factors affecting digital transformation and organizational innovativeness in NCR (India). Third, this article extends the former literature by the academic need for more investigation on digital transformation and its effect on the performance of businesses (Verhoef et al., 2021). Accordingly, this study enriches this academic conversation by introducing digital transformation (Abdurrahman et al., 2024) and organizational innovativeness (Mai et al., 2024) as mediators that may help SMEs improve their financial performance. Finally, this article can be used for future strategy formulation and regulatory planning by governments and institutions.

The article contains numerous sections. Firstly, Section 2 exhibited the theoretical underpinning and hypothesis. Section 3 outlines the research methods. Section 4 reports the findings. Section 5 provides the discussion, implications and future directions.

Digital transformation is a specific initiative to transform organizations, incorporating digital innovation and strategically administering key resources and core competencies to boost organizational performance (Abdurrahman et al., 2024). Recognizing the complex and multifaceted digital transformation process, Verhoef et al. (2021) outline the progress through three distinct stages: “digitization”, “digitalization” and “digital transformation.” Digitization encompasses converting data into a digitized form. Digitalization comprises how digitalized technologies and IT can transform business operations. Digital transformation is the mature phase, enabling enterprise-level transformations that lead to the development of innovative business models. Since business digitalization and innovation are complex and challenging processes with a lower rate of success - only about 10% of SMEs successfully undergo digital transformation - this poses a significant question for both business executives and academics (Mai et al., 2024). Thus, how these recent innovations and digital transformation improve performance is relevant for academics and practitioners. Additionally, in today’s contemporary world, digital transformation has been utilized across several disciplines, e.g. textile industries (Tsai & Su, 2022), real estate, banking (Al Issa & Omar, 2024; Abdurrahman et al., 2024), and the technological sector. However, despite its growing significance, scholarly work on SMEs’ role in digital transformation is still scarce. Furthermore, Eller, Alford, Kallmünzer, and Peters (2020) examined digitalization in Austrian SMEs and emphasized the need for additional research on SMEs in different regional and economic contexts. Consequently, this paper aims to close the gap by measuring the factors affecting the acceptance of digital transformation among small Indian enterprises.

Digital transformation involves the progression through which organizations leverage emerging digital technologies, including the internet and cloud-based solutions, to optimize operational efficiency. Some researchers have emphasized on examining organizational capabilities and resources from the perspective of digital transformation and organizational innovativeness. For instance, Mai et al. (2024) found that government policies and information technology (IT) capabilities are the key elements driving innovativeness and digital transformation. IT capabilities empower an enterprise to perform value-added functions that are critical for achieving optimal performance (Mai et al., 2024). Similarly, Mettler et al. (2024) concluded that governments’ policies actively influence the transformational process by establishing legal boundaries. Clearly, in addition to factors such as value co-creation and digital innovation, they have also been proven to be vital for enhancing digital service capability (Hongyun et al., 2023). Some scholars believe that market pressure also has a significant role in digital transformation (Zhang, Chu, Zhang, & Wang, 2023). In light of existing research on individuals’ resistance to adopting novel innovations, Kwangsawad and Jattamart (2022) call for more research to investigate the effect of technological anxiety. As identified by several scholars, Hausberg et al. (2019) and Aggarwal et al. (2024), the factors affecting digital transformation and organizational innovativeness of the firm should be further investigated. Accordingly, this work strives to bridge the gap by investigating the factors influencing the acceptance of digital transformation and organizational innovativeness among small enterprises.

RBV theory, proposed by Barney (1991), highlights the unique characteristics that facilitate constant growth to uphold a competitive advantage. However, due to the different research domains and diverse approaches, the domain of digital transformation is very challenging and complex to understand (Hausberg et al., 2019). Mai et al. (2024) exhibited that SMEs’ capability to thrive with larger organizations is scarce. In this context, governments deliver special initiatives, funds, guidance and regulations as part of their national economic strategies to boost SME development. Additionally, the RBV theory exhibited that organizations must enhance their IT capability by integrating their IT human resources, IT-enabled intangible assets and IT infrastructure to attain a competitive edge. Sometimes, environmental imposition exhibits the market pressure that small enterprises face from trading customers, partners and society when adopting novel technology (Ghobakhloo & Ching, 2019). Therefore, when firms want to gain a long period of success or improve their performance, they must focus on “valuable, rare, inimitable and non-substitutable (VRIN)” resources, such as IT capability, market pressure and government support, which are crucial in attaining competitiveness.

Co-creation is the synergistic process, integrated progression of generating novel value, symbolically and materially, through concurrent and peer-like interactions. Galvagno and Dalli (2014) studied the VCC theory, which concluded that institutions, actors and social forces influence value co-creation. Service research measured value co-creation as integrating existing resources with those from various service systems, contributing to overall well-being (Vargo, Maglio, & Akaka, 2008). Therefore, value co-creation is vital in determining digital transformation and organizational innovativeness to improve firms’ financial performance.

PET is fundamentally formulated to clarify how anxiety influences performance. Many SME entrepreneurs are not knowledgeable about information technology (Li, Su, Zhang, & Mao, 2018). PET can elucidate the effect of anxiety on performance through compensatory cognitive effort (Wilson, Smith, & Holmes, 2007). PET helps explain how anxiety impacts cognitive resources during changes like digital transformation, affecting an individual’s ability to process information and perform tasks.

In light of the above theories, this research focuses on the elements that contribute to digital transformation and organizational innovativeness, providing a more accurate understanding of firms’ financial performance.

IT capabilities are characterized by an enterprise’s capability to implement IT-driven resources that complement or coexist with other organizational resources. IT capabilities enable an enterprise to perform value-enhancing activities crucial for high performance (Mai et al., 2024). Earlier research exhibited that IT capabilities positively influence digital transformation and organizational innovativeness (Mai et al., 2024). Thus, the researchers posited that:

Value co-creation involves perceiving value through interactions, collaborative efforts or personalized experiences with a brand or stakeholders. Further, Hongyun et al. (2023) found that businesses involving their partners in value creation are more likely to implement digital transformation initiatives successfully. Earlier research exhibited that value co-creation positively influences digital transformation (Hongyun et al., 2023) and technology innovation (Huynh, Van Nguyen, Nguyen, & Dinh, 2023). The authors thus posit that:

As per Zhang et al. (2023a), market pressures in the external business environment are key factors driving firms’ digital transformation. Indeed, enterprises are encountering increasing market pressures, e.g. talent competition and technological innovation. Prior research has postulated that market pressures are vital to transformation intention (Zhang et al., 2023a). Further, Lee, Ginn, and Naylor (2009) exhibited that competitive pressure positively affects organizational innovativeness. Similarly, Zhang et al. (2023a) reported that external pressures positively influence corporate digital transformation intentions. Thus, the authors posited:

Technological anxiety is a psychological factor that could potentially elucidate resistance to innovation, especially for digital services (Mani & Chouk, 2018). Technological anxiety may cause uncertainty in task execution, decreased motivation and a weakened sense of capability. Earlier research by Gelbrich and Sattler (2014) reported that technological anxiety negatively influences self-service technology adoption. Thus, the researchers posited:

Government subsidies, indirectly or directly, can offset the lack of innovation input, enhancing technological innovation capabilities (Mai et al., 2024). These subsidies provide additional income to enterprises to support the research & development (R&D) initiatives. Earlier research by Mai et al. (2024) reported that government policies positively influence innovativeness. Similarly, Zhang et al. (2023b) also exhibited that policy support positively influences digital transformation. However, the same study reported that the fundamental mechanisms by which the government fosters digital transformation and innovation remain little examined. Accordingly, the research posited:

Digital transformation comprises leveraging novel digitalized technologies to optimise operational procedures and advance creative business approaches. A significant rise in digital transformation investment is evident across several industries (Al Issa & Omar, 2024). Further, Mai et al. (2024) reveal that organizational innovativeness positively influences firm performance. Empirical evidence from several studies suggests a positive relationship between digital transformation and bank performance (Abdurrahman et al., 2024), innovation performance (Hongyun et al., 2023) and firm performance (Mai et al., 2024). Hence, we posited that:

Innovation and disruption are the cornerstones of digital transformation (Al Issa & Omar, 2024). Embracing a proactive IT approach allows businesses to quickly identify and seize IT innovation opportunities to meet evolving information needs and business strategies (Mai et al., 2024). Further, Hongyun et al. (2023) found that digital transformation mediates the relation between value co-creation and innovation performance. Earlier scholarly work by Mai et al. (2024) reported a partial mediation of IT capabilities in the link between innovativeness and firm performance. Similarly, the same study reported that digital transformation serves as a full mediator in the relation between innovativeness and firm performance. Drawing from the literature, this article also posited that driving digital transformation mediates between various factors and firms’ financial performance. Hence, this research posited:

Innovativeness is vital for SMEs, as it empowers organizations to develop novel and improved processes and services essential for maintaining competitiveness (Abdurrahman et al., 2024). It has attracted considerable attention as an emerging engine of economic growth (Mettler et al., 2024). Earlier scholarly work by Abdurrahman et al. (2024) reported that innovation exerts a partial mediator between ecosystem capability and digital transformation. Hence, built upon these logical and rational claims, the current paper fills the gaps by analysing the mediating impact of organizational innovativeness in the link between digital transformation and firms’ financial performance. Hence, the researchers posited:

This article has selected eight variables, as demonstrated in Figure 1, which delivers an in-depth comprehension of the interconnection and rationale behind the selection of each variable.

All inquiries were formulated from previous research results (e.g. Mani & Chouk, 2018; Maroufkhani, Tseng, Iranmanesh, Ismail, & Khalid, 2020; Kwangsawad & Jattamart, 2022; Hongyun et al., 2023; Zhang et al., 2023a; Abdurrahman et al., 2024; Mai et al., 2024) and were modified to correspond with the research objectives (see Appendix A). The researchers organized group discussions involving six managers from six distinct SMEs and two academicians. The questionnaire was modified to suit the research context within SMEs using the feedback obtained from the discussion. After these modifications, the questionnaire was assessed through a pilot survey involving 69 respondents. Certain questionnaire items were further altered based on the respondents’ feedback to fit the research setting. The pilot survey indicated that “Cronbach’s alpha (CA)” value for all constructs exceeded 0.7, indicating acceptable reliability (Hair, Ringle, & Sarstedt, 2011). All items were verified on a “seven-point Likert scale” from 1 to 7 here, “1 indicates absolutely disagree” and “7 indicates absolutely agree”, as utilized by Kumar, Rani, Rani, and Rani (2025a, b, c).

The researchers adopted a “self-administered questionnaire survey” to collect the data accurately. The data were gathered from SME managers and owners of NCR (India) as the unit of analysis, which encompasses “Rajasthan (2 districts), Uttar Pradesh (8 districts), Delhi and Haryana (14 districts)” (NCRPB, 2017). NCR people come from diverse areas of India, sparking its nationwide diversity. Thus, the findings are more generalizable and extensively applicable. Further, SMEs are pivotal to economic development in many countries within the Asia-Pacific region, including India (Rakshit, Islam, Mondal, & Paul, 2022), accounting for 40% of total exporting and 45% of total industrial manufacturing, which contributed to India’s GDP. From another perspective, Indian SMEs proactively adapt their plans to achieve economic growth; thus, SMEs are considered the backbone of our nation’s societal and economic advancement. Therefore, the paper on digital transformation in Indian SMEs suits the research context.

The research thoughtfully chose target enterprises to accurately represent the broader population and ensure that the findings could be generalized across the broader community. The selected enterprises must initially align with the Ministry of “Micro, Small and Medium Enterprises” define SMEs as having a maximum annual business volume of Rs. 50 crore and machinery and plant investments limited to Rs. 10 crores. Building upon the academic contributions of Kumar et al. (2024), two screening questions were applied to determine participant eligibility: Are you currently employed in SMEs? and do you possess one year of experience in your respective SMEs? Only participants who selected Yes for both questions were included in the study. Additionally, we employed the purposive sampling method to gather responses. The managers and owners were briefed regarding the study’s purpose and assured confidentiality. The survey responses were gathered from March 2024 to June 2024. Around 1050 SME managers and owners were humbly requested to respond during the data collection. However, out of those, only 550 gave their responses on the condition of anonymity and for academic use of data. Of the 550 survey questionnaires, 39 respondents were excluded due to incomplete data and outliers and 511 responses were deemed valid for further analysis. As emphasized by Cooper, Schindler, Cooper, and Schindler (2006) and Vafaei-Zadeh, Nikbin, Seong Zhen, and Hanifah (2025), a suitable sample size for academic research typically falls between 40 and 400 participants. To ensure statistical adequacy, we conducted a power analysis using G*Power software, considering an effect size of 0.06 and six independent variables. The analysis indicated that a minimum of 219 participants would be required to achieve sufficient statistical power. Additionally, we followed the guideline proposed by Hair et al. (2011), which advocates for a minimum sample size equivalent to ten times the number of measured indicators. Given our model included 26 indicators, the required minimum was 260 respondents (26*10 = 260). By employing both power analysis and established structural modelling guidelines, we adopted a multi-step, methodologically sound approach to sample size determination. This enhances the robustness, reliability and generalizability of our findings. Out of 511 respondents, 88.84% were males, 44.62% were post-graduated and the majority, 50.49%, had experience of 1–3 years. Table 1 exhibits the details of the sample characteristics.

Before executing the measurement model, the study ensures the absence of CMB. For this, the authors conducted two statistical tests: Firstly, we employed Harman’s single-factor analysis under the guidance of Kumar et al. (2025a, b). The findings indicated that the initial factor captured 22.36% of the variance, falling short of the required 50% benchmark, signifying that CMB was not a critical problem. Secondly, a VIF value below 5 implies that multicollinearity is not an issue in the latent constructs (Hair, Risher, Sarstedt, & Ringle, 2019). Accordingly, the VIF value in this study falls beneath the threshold, confirming the model’s robustness (see Table 2).

This article adhered to the procedure of Armstrong and Overton (1977) to assess non-response bias. To measure this, the current study compared 125 early and 115 late respondents. T-tests were executed at a 95% confidence interval to measure whether there were substantial differences between late and early respondents. The empirical analyses demonstrated no substantial differences between the two segments, implying that “non-response bias” is not a major issue.

The PLS-SEM technique was selected for its adaptability and effectiveness during the analysis phase. PLS-SEM is widely utilized in the social sciences, particularly for complex frameworks with intricate relationships among multiple constructs (Hair et al., 2019), given that this article aims to examine interactions among various constructs within the novel theoretical model.

The measurement model conducted a “confirmatory factor analysis” to evaluate the validity and reliability of the constructs. In Table 2, the reliability of indicators was ensured by the outer loading of each item. Hair et al. (2019) state that CA and “composite reliability (CR)” values should range from 0.7 to 0.95. Thus, the CA values (0.783–0.841) and CR (0.845–0.905) fall within the recommended range, indicating confirmed data validity and reliability.

Furthermore, all constructs demonstrated convergent validity, with their “average variance extracted (AVE)” values surpassing the threshold of 0.50, as recommended by Hair et al. (2011). The AVE ranging from (0.602–0.761) signifies that the items assessing the same constructs explain more than 50% of the variance. Discriminant validity was assessed utilising the “Heterotrait–Monotrait (HTMT)” ratio. According to Legate et al. (2023), discriminant validity between all constructs is confirmed when HTMT values are below the proposed cut-off of 0.90. Thus, the HTMT values in this study were lower than the suggested threshold, satisfying the convergent validity criterion (refer to Table 3 for details).

Figure 2 explains the structural model derived from the PLS analysis, demonstrating how the variance of endogenous variables (R²) and the standardized path coefficient (β) contribute to explaining the outcomes of the structural model. R² values of 0.75, 0.50 and 0.25 are significant, moderate and weak, respectively (Hair et al., 2011). The model’s validation involved assessing the R² values, while the t-statistics were established through a bootstrap method employing 5,000 samples. The structural model explained 56% of the variance in digital transformation (R² = 0.560), 68.8% in organizational innovativeness (R² = 0.688) and 54.4% in firms’ financial performance (R² = 0.544). All R² values were considered satisfactory.

Table 4 and Figure 2 present the outcomes of testing the research hypotheses. Initially, the structural model reveals that IT capability positively relates to digital transformation and organizational innovativeness with (β = 0.337***, t = 7.366) and (β = 0.132*, t = 3.039); thus, H1a and H1b are confirmed. Secondly, the findings demonstrate that value co-creation also positively influences digital transformation and organizational innovativeness, with (β = 0.097*, t = 2.677) and (β = 0.431***, t = 10.737); therefore, H2a and H2b are supported.

Thirdly, market pressure is positively related with digital transformation and organizational innovativeness, with (β = 0.444***, t = 10.174) and (β = 0.111*, t = 2.919); hence, H3a and H3b are supported by the SEM model. However, technological anxiety demonstrates an insignificant relationship with digital transformation and organizational innovativeness, with (β = 0.030^ns, t = 0.994) and (β = −0.032^ns, t = 1.270); therefore, H4a and H4b are not supported. Furthermore, the findings suggest that government policies positively impact digital transformation and organizational innovativeness, with significant path coefficients of (β = 0.074*, t = 2.366) and (β = 0.078*, t = 2.545), thus supporting H5a and H5b. Moreover, digital transformation significantly influences organizational innovativeness with (β = 0.351***, t = 6.744) and firm financial performance with (β = 0.432***, t = 10.674). Finally, organizational innovativeness (H6c) is confirmed by the testing outcomes with (β = 0.371***, t = 8.872), verifying H6a, H6b and H6c hypotheses.

Mediation tests were conducted to investigate whether digital transformation and organizational innovativeness mediated the relation between financial performance. The mediation analysis depicts that the indirect effect of Technological anxiety → digital transformation → Organizational innovativeness (β = 0.012^ns, t = 0.962) has an insignificant impact on Organizational innovativeness. In Table 4, all the hypotheses were supported except (H7d), which ensured the presence of mediation.

Digital transformation has drawn considerable attention for facilitating streamlining operations and promoting enterprise innovation; nevertheless, researchers have paid limited attention to entrepreneurs’ acceptance of digital transformation to develop Innovative business approaches. To close this gap, this article formulates a conceptual framework, which suggests that the variables, e.g. digital transformation and organization innovativeness, are crucial in influencing the financial performance of small enterprises, which has been studied by examination of various independent variables. This part discusses the outcomes of the proposed research hypotheses.

Response to RQ1: The study found that IT capabilities (H1a and H1b) positively influence digital transformation and organizational innovativeness, consistent with Mai et al. (2024). This implies that SMEs with robust IT systems and resources, precise planning and vision and a proactive approach to R&D have a greater possibility of implementing digital transformation effectively. Moreover, value co-creation positively influences digital transformation (H2a) and organization innovativeness (H2b), coherent with Hongyun et al. (2023). This suggests that transparent and collaborative processes between SMEs and their stakeholders help to co-create value and advance digital transformation initiatives. Likewise, market pressure positively influenced digital transformation (H3a) and organization innovativeness (H3b). The findings are coherent with the academic contributions of Zhang et al. (2023a), who concluded that market pressure promotes the transformation intention of SMEs. This implies that external pressures encouraged SMEs to utilize digital (Omrani et al., 2022) and greener transitions, which increasingly converge in modern business environments. Market pressure creates a sense of urgency, even when SMEs have limited resources, pressuring them to hold digital transformation as a strategic asset to adapt, compete and thrive in today’s digital economy. Regarding hypotheses (H4a and H4b), the study results suggest that technological anxiety has a statistically insignificant impact on digital transformation and organization innovativeness. This is coherent with the results of Kwangsawad and Jattamart (2022), who exhibited that technological anxiety is a potential barrier to individual innovation. This indicated that technological anxiety (e.g. fear of making irreversible mistakes and lack of familiarity with new technology) could lead to hesitation in adopting digital transformation and organizational innovativeness for SMEs. A greater level of anxiety within a particular technology tends to limit innovation in small enterprises. Moreover, government policies are positively influencing digital transformation (H5a) and organization innovativeness (H5b), coherent with (Mai et al., 2024). This assertion indicates that the government offers essential technology and provides enterprises with accessibility to its extensive resources (monetary and non-monetary), enabling enterprises to implement digital transformation collaboratively.

Response to RQ2: Regarding hypotheses (H6a, H6b and H6c), the outcomes depict that there is a substantial association between digital transformation, organizational innovativeness and the financial performance of the firm, coherent with Hongyun et al. (2023), Abdurrahman et al. (2024). Accordingly, enterprises may recognize the significance of technological capabilities in attaining competitive advantage and become more inclined to improve their performance. The results can be the groundwork for upcoming research that explores additional insights into digital transformation in developing and developed nations.

This paper delivers remarkable contributions to the prevailing literature on the digital economy in a particularly unique and noteworthy manner. Firstly, in the present age, digital transformation represents one of the underexplored research areas in the service discipline (Hausberg et al., 2019; Verhoef et al., 2021). Accordingly, our study contributes to the scholarly landscape by highlighting the impact of contextual factors (e.g. IT capability, value co-creation, market pressure, technological anxiety and government policies) on organizational innovativeness and digital transformation.

Second, the research advances existing scholarly knowledge on digital transformation by integrating three theories, i.e. RBV theory, value co-creation theory and process efficiency theory for examining firm financial performance. The RBV theory asserts that a firm’s collection of resources can enhance its competitive advantage, depending on the specific qualities and strengths of those resources (Barney, 1991). In context, Taher (2011) states that a firm can be seen as a collection of resources and capabilities that support its continued existence and growth. In the context of SME, IT capabilities, market pressure and government support are the resources that help in promoting digital transformation and organizational innovativeness, which ultimately enhance firm financial performance. Additionally, value co-creation theory suggests that value is jointly devised by enterprises and consumers through complex and dynamic processes (Xie, Wu, Xiao, & Hu, 2016). In this study, digital transformation and organizational innovativeness represent an important channel for firms to co-create value with customers. According to process efficiency theory, cognitive anxiety decreases the efficiency of working memory, reducing both its processing and storage capabilities and consequently restricting the cognitive resources needed for a given task (Wilson et al., 2007). In SME’s, technological anxiety can create hesitation or resistance within organisations, making it harder to embrace innovation and digital transformation. In the course of adopting technological solutions, Shetty and Panda (2023) highlight that the impact of emerging technologies in a particular context cannot be explained by a single set of determinants. A holistic understanding of these interconnected factors is essential for effective and sustainable technology adoption. Therefore, this study integrates three theoretical frameworks to obtain more robust insights into firm financial performance.

Thirdly, the majority of extant studies in the service field only measure digital transformation (e.g. Abdurrahman et al., 2024; Hongyun et al., 2023) and organizational innovativeness (e.g. Lee et al., 2009) separately, but there is a dearth of existing research that can concurrently capture both digital transformation and organizational innovativeness as a mediating mechanism in the enhancement of financial performance. Fourthly, as per Hongyun et al. (2023), SMEs are major contributors to national and regional employment, innovation and job creation. Nevertheless, earlier studies have mainly emphasized large enterprises, while the conditions within SMEs remain insufficiently investigated (Ghobakhloo & Ching, 2019). Consequently, this research seeks to close the existing gap by assessing the factors affecting organizational innovativeness and digital transformation and its effect on the financial performance of small Indian enterprises. In conclusion, the results lay the groundwork for future investigations aimed at gaining additional insights into digital transformation in developing and developed nations.

Drawing from the study’s findings, we have identified several recommendations for practitioners regarding digital transformation and the financial performance of an enterprise. The evidence points to technological anxiety as a primary obstacle to innovation and digital transformation utilization. These issues can be linked to concerns regarding accidental transactions, e.g. data loss risk and fear of making irreversible mistakes. Therefore, managers need comprehensive training and education programs to mitigate or minimize the technological anxiety faced by SMEs and facilitate the successful utilization of digital innovation within their organizations. The findings depict that market pressure is a significant concern for encouraging innovation and digital transformation among SMEs. Yet, a significant portion of resource-limited SMEs do not possess the necessary competencies to cope with this degree of complexity (Eller et al., 2020). Accordingly, SME managers facing constant market pressure should adopt lean innovation to test and validate digital transformation strategies with minimal investment. The results highlight the strategic importance of strengthening IT capabilities within organisations. Firms should focus on building robust IT infrastructure, enhancing technical skills and fostering IT-business alignment to support digital transformation and drive innovation. By doing so, organizations can improve their adaptability, streamline operations and create value-added processes that contribute directly to improved financial performance.

In addition, government support is a prominent construct in enhancing digital transformation and organizational innovativeness, which ultimately enhances firm financial performance. By creating a favourable regulatory environment and providing access to digital resources, governments can help firms overcome barriers to innovation, enhance competitiveness and ultimately improve their financial performance. Based on our study’s findings, governments can implement additional measures to support innovation and digital transformation in SMEs by employing digital outreach programs or innovative application development plans. Furthermore, the results highlight the significance of value co-creation in enhancing financial performance. Businesses should encourage active collaboration with customers, employees and partners to jointly develop products, services and solutions. This not only strengthens relationships and trust but also leads to more innovative and customer-centric offerings. By integrating co-creation into their strategy, firms can improve customer satisfaction, differentiate themselves in the market and achieve stronger financial outcomes. These insights not only deepen our understanding but also offer helpful, real-world advice for SME to succeed in the digital era. Thus, SME managers should upskill employees in digital competencies to ensure smoother adoption of technological advancements and enhance financial performance.

The emergence of digital transformation as a novel technological system has significantly transformed the global business landscape. Organizational resources are scarce (Eller et al., 2020) and competition increases daily; enterprises strive to utilize novel technologies in the digital innovation and transformation era. Accordingly, this research explores the factors influencing organizational innovativeness and digital transformation that would help achieve financial performance using a revolutionary PLS-SEM approach. The results answered the research questions and exhibited that each variable meaningfully contributed to organizational innovativeness and digital transformation (except H4a and H4b). The signifies that IT capabilities (e.g. possesses the capability for IT infrastructure), value co-creation (e.g. communicates long-term plans with the supplier/client), market pressure (e.g. suppliers uphold stringent green standards) and government policies (e.g. laws and regulations adequately safeguard implementation of digital transformation) are important to enhance the organizational innovativeness and digital transformation. However, technological anxiety (e.g. hesitation to adopt technology due to unfamiliarity) has resulted in lower innovation and digital transformation levels. In the Indian context, SMEs often exhibit reluctance to utilize novel technology. The authors believe that improving the workplace environment through innovation and technological transformation ensures a competitive position and helps achieve Sustainable Development Goals.

This study draws significant conclusions with specific theoretical and managerial implications while acknowledging several limitations that could guide future research. First, the dataset used in this survey was sourced from an emerging market such as India; thus, future researchers can consider more respondents from other nations, encompassing different regulatory environments. Additionally, empirical analysis based on cross-sectional data cannot fully address issues of causation and dynamics. Thus, a longitudinal study utilising data from various sources, including secondary and primary data, is recommended to investigate upcoming causality research.

The supplementary material for this article can be found online.