Original Research

Digital transformation for sustainable business performance in small and medium enterprises

Ralebitso Kenneth Letshaba, Lebogang T. Mosupye-Semenya

Received: 01 Oct. 2025; Accepted: 08 June 2026; Published: 20 Aug. 2026

Copyright: © 2026. The Authors. Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Purpose: This study examines the influence of digital transformation (DT) on the sustainable performance of Small and Medium Enterprises (SMEs) in South Africa. Digital transformation is gradually identified as a driver of competitiveness, allowing businesses to adjust to technological and market changes.

Design/methodology/approach: A quantitative, cross-sectional survey was used for the study, drawing responses from a sample size of 213 SME owners and managers in the City of Matlosana Municipality, South Africa. Respondents were identified through a random sampling method. Hypothesised relationships were examined using Structural Equation Modelling with Smart-Partial Least Squares as the analytical tool.

Findings/results: The results show that Digital Intensity significantly and positively influences financial, environmental, and social performance (SP), highlighting its role as a primary driver of SME sustainability. In contrast, Transformation Management Intensity shows no significant effects across these performance dimensions, suggesting that managerial effort without robust digital capabilities is insufficient to deliver measurable sustainability outcomes.

Practical implications: The study contributes to Resource-Based View by demonstrating that digital resources function as critical enablers of long-term competitiveness and sustainability in SMEs. For practice, these findings underline the need for prioritising investment in digital tools and skills. Policymakers and support agencies should consider targeted initiatives, including training, funding and infrastructure support, to address barriers that constrain SME DT.

Originality/value: The study offers empirical data from a developing market, integrating financial, environmental and SP into the examination of DT. It advances current debates by distinguishing between the roles of digital resources and managerial transformation efforts in shaping SME sustainability.

Keywords: digital transformation; SMEs; sustainable performance; South Africa; Resource-Based View; digital intensity; transformation management intensity.

Introduction

The Fourth Industrial Revolution (4IR), largely shaped through digital transformation (DT), is advancing at an unprecedented pace. At its core, DT involves the integration of digital attributes such as replication, connectivity, simulation and feedback to reconfigure operations and decision-making (Teng et al., 2022). Unlike digitisation or isolated technology adoption, DT represents a holistic shift that reshapes business models, customer engagement, and organisational culture, compelling firms to innovate and remain resilient in rapidly changing environments. In developing countries, Small and Medium Enterprises (SMEs) are crucial in poverty alleviation, inequality reduction and job creation (Adelowotan, 2021; Serumaga-Zake & Van der Poll, 2021). Within South Africa, SMEs are central to employment and local development (Du et al., 2025). Embracing DT can increase productivity and efficiency (Serumaga-Zake & Van der Poll, 2021) and strengthen competitiveness and sustainability (Alojail & Khan, 2023). Some argue that SMEs in developing economies can leapfrog earlier industrial stages by directly adopting 4IR technologies (Adegbite & Govender, 2021).

Yet many SMEs remain at the margins of DT. Advanced capabilities are concentrated in large firms (Lorenz & Kraemer-Mbula, 2021), and persistent human, technical and financial constraints hinder SMEs from moving beyond piecemeal adoption to integrated transformation (Rupeika-Apoga & Petrovska, 2022). Structural characteristics further limit readiness to reconfigure business models (Gumbi & Twinomurinzi, 2020). Similar barriers are reported in developed contexts: SMEs in Korea and the UK recognise the importance of 4IR but face resource gaps, knowledge deficits and weak strategic alignment (Masood & Sonntag, 2020). This has prompted growing attention to DT in SMEs, spanning technical efficiency (Feng et al., 2022), supply chain resilience (Munongo & Pooe, 2022), opportunities and barriers (Antoniuk et al., 2017), organisational readiness (Gumbi & Twinomurinzi, 2020), and performance effects (Alqam & Saqib, 2020). In developed economies, work has also examined implementation frameworks (Mittal et al., 2018), awareness (McFarlane et al., 2024) and barriers (Olszewska, 2020). However, a clear empirical gap remains in direct links between DT and sustainability, economic, environmental and social, which are underexplored in resource-constrained SME settings such as South Africa.

Sustainability is increasingly treated as a multidimensional performance goal, with firms under stakeholder pressure to integrate environmental and social responsibility alongside financial outcomes (Crittenden et al., 2011). Digital transformation offers a path for SMEs to embed sustainability, optimising resources, reducing waste and improving transparency, while building trust and long-term customer loyalty (El-Kassar & Singh, 2019). Yet many SMEs lack structured strategies, opting for short-term technological fixes rather than embedding DT within a coherent roadmap for sustainable growth (Sun et al., 2024). This underscores a key knowledge gap: DT is often studied for agility and competitiveness, but its role in enabling sustainable business performance in SMEs remains under-examined (Cardoso et al., 2023; Syarkani, 2025).

Although research on DT and sustainable business performance in SMEs has expanded substantially, three significant gaps persist (Costa Melo et al., 2023; Gil-Gomez et al., 2020; Karikari et al., 2025; Savastano et al., 2022; Yuen & Baskaran, 2023). Firstly, most scholars examine DT in relation to the adoption, readiness or operational efficiency, with limited empirical evidence connecting DT capabilities to multidimensional sustainability outcomes in resource-constrained emerging economies. Secondly, prior studies are likely to consider DT as a one-dimensional construct, failing to notice the interaction between technological intensity and managerial transformation capabilities. Thirdly, evidence from sub-Saharan Africa, particularly South Africa, remains scarce regardless of its structurally constrained yet innovation-driven SME environment.

Addressing the identified gaps, this study contributes by: (1) empirically examining the relationship between digital intensity (DT) and transformation management intensity (TMI) and sustainable business performance across economic, environmental and social dimensions; (2) extending the Resource-Based View (RBV) by conceptualising DT as a configuration of digital and managerial capabilities rather than mere technology adoption; and (3) presenting context-specific evidence from South African SMEs, thus enriching DT scholarship with understandings from a developing economy setting.

In South Africa, these challenges are intensified by financial constraints, infrastructure gaps and volatile markets (Hanelt et al., 2021; Sharabati et al., 2024), reinforcing calls for context-specific approaches attuned to SME realities (Martínez-Peláez et al., 2024). Underpinned by the RBV, the study seeks to understand how two firm-level resources and capabilities associated with DT, Digital Intensity (DI) and TMI, relate to sustainable business performance in South African SMEs. The study seeks to address the following research questions:

To what extent is DI connected to financial, environmental, and social performance in SMEs?

To what extent is TMI connected to financial, environmental, and social performance in SMEs?

By framing the inquiry in this way, the study moves beyond the adoption-versus-non-adoption debate to consider how SMEs can leverage digital and managerial capabilities to entrench sustainability into the operations of the enterprise. The remainder of the study is organised as follows: The literature review on DT and business performance, along with the theoretical framework and hypotheses; the research methodology; the results and discussion; and finally, the conclusion, which highlights implications and directions for future research.

Literature review

Digital transformation

Digital transformation refers to an organisation-wide reconfiguration enabled by digital technologies consisting of artificial intelligence, cloud computing and analytics, which fundamentally modify how businesses create and attain value (Saeedikiya et al., 2025; Warner & Wäger, 2019). More than the adoption of isolated tools, DT reflects a holistic shift in strategy, culture and capabilities that reshape business models, customer engagement and decision-making. Scholars distinguish between digitisation, digitalisation and DT. Digitisation denotes to the transformation of analogue data into digital formats, whereas digitalisation includes automating and optimising processes using digital tools (Chisita et al., 2021). Digital transformation, in contrast, entails deliberate and strategic changes across the organisation that extend to business models, governance and organisational culture (Nasiri et al., 2022; Ranawaka & Said, 2024). In this sense, DT reflects not only the utilisation of technology but the integration of organisational and managerial capabilities to achieve sustainable competitive advantage. In the setting of this study, DT is evaluated through DI and TMI.

Digital intensity

Digital intensity is a key component of DT, crucial for achieving digital maturity and sustainability (Nasiri et al., 2022). Digital intensity is the degree to which firms embed digital solutions into core operations. It captures the breadth and depth of digital adoption, from e-commerce to data analytics, and serves as an indicator of how far firms have progressed in embedding digital processes (Burinskienė & Seržantė, 2022; Criveanu, 2023). At the macro level, studies demonstrate that higher DI contributes to competitiveness, productivity and growth, with evidence from European Union (EU) countries showing that SMEs with greater DI are more resilient and innovative (Silva & Rkibi, 2024). Digital intensity enables businesses to operate more effectively and manage greater amounts of tasks in dynamic environments by embracing technology-driven changes (Westerman et al., 2012). According to Sousa-Zomer et al. (2020), DI has a major impact on DT and is associated with better business performance. Additionally, it provides a framework for resolving issues and developing winning tactics in DT initiatives.

Transformation management intensity

Transformation management intensity, on the other hand, reflects the organisational and managerial effort invested in driving and coordinating transformation. It involves leadership commitment, cultural readiness and strategic alignment that enable firms to mobilise digital resources effectively (Liang et al., 2022; Mwangi & Mang’ana, 2024). According to Westerman et al. (2012), TMI is described as the ability to drive meaningful change. It involves having a clear vision for a new and improved future, establishing strong governance and engagement to guide and manage the process, and building effective collaboration between digital technology and business teams to successfully implement technology-driven changes. Organisations with strong TMI are defined not only by having a clear vision for transformation, but also by a governance structure and organisational culture that actively coordinate digital initiatives and ventures to achieve the greatest possible business impact (Kwiotkowska, 2024).

Sustainable business performance

In this study, sustainability is understood as the capacity to maintain performance at a consistent level over time, extending beyond financial outcomes to encompass social and environmental responsibilities (Wentzel et al., 2022). Sustainable business performance reflects how effectively firms organise their functions, processes, and resources to achieve long-term viability, environmental stewardship and social well-being. Central to this perspective is the strengthening of stakeholder relationships, particularly with employees, customers and regulators, whose expectations increasingly shape organisational legitimacy (Liu et al., 2023). The triple bottom line framework (Elkington & Rowlands, 1999) remains a dominant approach for conceptualising sustainability, requiring firms to balance financial performance (FP) with environmental integrity and social value. Recent studies highlight that SMEs’ ability to meet these three dimensions is directly linked to their competitiveness, innovation capacity and social legitimacy (Belhadi et al., 2022; Kwiotkowska & Gębczyńska, 2021).

Financial performance

Financial performance refers to a firm’s capacity to generate positive economic outcomes that support profitability, growth, and long-term sustainability. For SMEs, maintaining strong FP is important not only to meet the expectations of business owners but also to ensure the continuity of operations and to create ongoing value for stakeholders over time (Bartolacci et al., 2020). According to Ahinful et al. (2023), FP essentially contributes to the survival and growth of businesses, as financial resources serve as the lifeblood that supports daily operations. When a firm experiences poor FP or lacks sufficient financial resources, it may face financial distress, which can hinder its operational efficiency and limit its potential for growth. In this study, FP is assessed using indicators related to profitability and growth, such as profit growth, sales or revenue growth, return on sales and return on assets.

Environmental performance

Environmental performance (EP) refers to how well a firm manages and reduces the negative impact of its operations, products, and processes on the natural environment. This concept has become an important concern for businesses because of increasing environmental challenges, regulatory requirements and stakeholder expectations. Firms are therefore encouraged to incorporate environmental considerations into their strategies to improve both financial and non-financial outcomes (Zahoor & Gerged, 2021). Additionally, EP is reflected in actions and results such as lowering the environmental impact of products and services, reducing operational waste and emissions, conserving energy, limiting pollutants and using water more efficiently (Rehman et al., 2022).

Social performance

Social performance (SP) refers to how organisations address and improve issues related to civil rights, public health, safety and community support initiatives. It focuses on the responsible management of people and social capital and forms an important component of the triple bottom line approach to sustainability within organisations (Kumar et al., 2024). Observed evidence suggests that SP can be assessed through indicators such as product responsibility. This includes practices related to data privacy protection, quality management systems, initiatives that support economically disadvantaged consumers and broader corporate social responsibility activities promoted by organisations (Matemane et al., 2024).

Theoretical framework: Resource-based view

The RBV suggests that firms sustain a competitive edge through deploying internal assets and capabilities that competitors cannot easily imitate (Barney, 1991). These internal assets are tangible, such as infrastructure, or intangible, like skills, knowledge and organisational ethos, but their strategic value lies in how they are configured to deliver long-term performance (Barney et al., 2011). The RBV suggests that DT helps firms use technology and information more effectively, improving efficiency, adaptability and long-term competitiveness (Wu et al., 2025). Recent research continues to apply RBV to explain how organisations leverage digital resources and organisational capabilities to achieve resilience and sustained performance in dynamic environments (Khurana et al., 2022; Yi et al., 2023; You et al., 2023). Resource-Based View, therefore, provides an appropriate theoretical lens for examining how technological resources and organisational capabilities associated with DT contribute to sustainable business performance in SMEs.

Within this study, DI is conceptualised as a technological resource. It captures the breadth and depth of digital tools embedded into operations, ranging from cloud computing and analytics to artificial intelligence and Internet of Things (IoT). As a resource, DI equips firms with the infrastructure to streamline processes, generate efficiencies and respond to customer needs more effectively (Burinskienė & Seržantė, 2022; Criveanu, 2023). Higher levels of DI are associated with innovation and competitiveness at both firm and economy-wide levels, as digital adoption enables more scalable and adaptable models of value creation (Chiappini & Gaglio, 2024; Li et al., 2023). Recent studies further demonstrate that DT can strengthen enterprise innovation resilience and organisational adaptability (Peng & Jia, 2024), while effective digital data management systems support SME scalability and growth in the South African context (Gaaje et al., 2025).

However, without complementary organisational capabilities, these technological resources often remain underutilised or fragmented, limiting their transformative potential. Transformation Management Intensity, by contrast, represents an organisational capability. It reflects leadership commitment, cultural readiness, and managerial effort directed towards aligning digital initiatives with broader strategic goals. Transformation Management Intensity determines whether digital resources are applied in ways that generate long-term value, facilitating cross-functional collaboration, organisational learning and the reconfiguration of existing routines (Belhadi et al., 2022; Mwangi & Mang’ana, 2024). Research increasingly highlights that successful DT in SMEs depends on the development of organisational competencies capable of guiding and coordinating transformation initiatives (Gonzalez-Varona et al., 2024). Similarly, studies on sustainable DT emphasise the importance of structured transformation management approaches for integrating technological innovation with organisational change (Mick et al., 2024).

Prior studies suggest that strong transformation management is essential to embedding digital solutions beyond compliance functions, enabling firms to integrate sustainability goals, improve supply chain resilience and foster inclusive practices (Kargas et al., 2024). The RBV offers a useful lens through which to look at how SMEs combine technological resources and organisational capabilities to achieve sustainable performance. Recent DT research supports this view, demonstrating that firms derive value from digital technologies only when they combine technological adoption with organisational capabilities that enable learning, coordination and strategic alignment (Egala et al., 2024; Scuotto et al., 2021). Grounded in this theoretical framing and the reviewed literature, the next section sets out the study’s hypotheses.

Hypotheses development

The hypotheses for the study are based on how DI and TMI, as conceptualised within the RBV, influence financial, environmental and reviewed in SMEs.

The relationship between digital intensity and financial performance in Small and Medium Enterprises

Digital intensity, defined as the extent to which businesses adopt and integrate digital technologies into their operations, is increasingly recognised as a factor that influences FP. Moro-Visconti et al. (2025) show that digital platforms improve revenue streams, reduce operating costs and enhance financial viability, with measurable impacts on Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA), market capitalisation, and debt financing capacity. Similarly, Nasiri et al. (2022) emphasise that while DI alone may not directly guarantee financial success, their effect is maximised when combined with digital maturity, which ensures long-term adaptability and structural readiness.

Research in the EU context also indicates that DI positively influences gross domestic product (GDP) and sustainable growth. Criveanu (2023) finds that high levels of DI, coupled with e-commerce, contribute significantly to economic competitiveness and performance across EU countries. Furthermore, empirical studies suggest that SMEs leveraging digitalisation are in a better position to secure scalability, efficiency and long-term competitiveness compared to those lagging (Burinskienė & Nalivaikė, 2024).

Thus, across multiple contexts, financial markets, firm-level operations and broader economic performance, the evidence suggests that higher DI enhances SMEs’ FP. Therefore, we hypothesise the following:

H1: There is a positive relationship between DI and financial performance in SMEs.

The relationship between digital intensity and environmental performance in Small and Medium Enterprises

Digital intensity extends beyond financial outcomes, influencing sustainability practices. Research demonstrates that DT enables firms to align with environmental objectives, particularly by reducing waste, improving resource efficiency and facilitating green innovation. Chen and Ren (2025) provide quantitative evidence that DT contributes significantly to Environmental, Social, and Governance (ESG) outcomes, with the strongest effects observed in EP. In the EU context, Burinskienė and Nalivaikė (2024) emphasise the importance of SMEs adopting digital solutions to meet Green Deal objectives. They argue that DI is critical for achieving ‘twin transformations’ digital and sustainable, thus reinforcing SMEs’ ability to meet environmental goals. Complementary evidence from Kargas et al. (2024) shows that, while Greek firms are still underutilising digital technologies for environmental purposes, digital management intensity contributes to emissions reduction and environmental risk prevention when strategically applied. Together, these findings suggest that greater degrees of DI can enable SMEs to improve their environmental footprint, aligning with broader sustainability targets. Therefore, we hypothesise the following:

H2: There is a positive relationship between DI and environmental performance in SMEs.

The relationship between digital intensity and social performance in Small and Medium Enterprises

Digital intensity also shapes the social dimension of performance, influencing issues such as transparency, inclusion, and stakeholder engagement. Chen and Ren (2025) highlight how DT improves social transparency and raises stakeholder expectations regarding corporate responsibility. Similarly, Burinskienė and Nalivaikė (2024) argue that SMEs undergoing twin transformations can achieve broader social benefits by embedding digitalisation within sustainability frameworks, contributing to social cohesion and equitable development. Criveanu (2023) reinforces this perspective, showing that DI can make financial, medical and educational services more accessible, thereby reducing inequality and contributing to socially inclusive growth. At the enterprise level, SMEs integrating digital practices not only strengthen competitiveness but also respond more effectively to societal needs, enhancing their legitimacy and social licence to operate. Taken together, these studies suggest that DI plays a meaningful role in shaping SMEs’ social outcomes by enhancing stakeholder engagement, promoting inclusivity and supporting community development. Therefore, we hypothesise the following:

H3: There is a positive relationship between DI and social performance in SMEs.

The relationship between transformation management intensity and financial performance in Small and Medium Enterprises

Transformation management intensity denotes the extent to which firms actively manage organisational change to leverage DT and dynamic capabilities. Evidence shows that effective transformation management enhances financial outcomes by aligning managerial capabilities with strategic renewal. Mwangi and Mang’ana (2024) demonstrate that dynamic managerial capabilities, like identifying opportunities, exploiting them and continuous renewal, significantly improve firm performance in the logistics sector, highlighting the direct financial benefits of transformation management. Similarly, Liang et al. (2022) show that adaptive and absorptive capabilities, when embedded within ESG and transformation strategies, positively impact sustainable management and create long-term financial advantage. Belhadi et al. (2022) add that transformation initiatives integrating Industry 4.0 capabilities with ambidextrous management practices lead to higher operational efficiency and economic resilience across global supply chains. These findings are echoed in Yu and Ramanathan (2016), who argue that functional and managerial capabilities are central to mediating environmental management practices, thereby indirectly improving both environmental and FP. Overall, these studies suggest that SMEs engaging in greater stages of TMI are better positioned to improve competitiveness, strengthen strategic flexibility and ultimately enhance FP. Hence, we hypothesise the following:

H4: There is a positive relationship between TMI and financial performance in SMEs.

The relationship between transformation management intensity and environmental performance in Small and Medium Enterprises

Transformation management intensity has also been acknowledged as a significant enabler of environmental sustainability outcomes. Wang and Teng (2022) demonstrate that DT, in conjunction with strong supply chain management capabilities, substantially improves EP in manufacturing firms. Similarly, Yu and Ramanathan (2016) find that transformation in operational and marketing capabilities supports environmental management practices, leading to improved EP. Belhadi et al. (2022) show that transformation management through Industry 4.0 initiatives fosters circular business models, which directly support emissions reduction, waste minimisation and sustainable resource use. De et al. (2024), in their study of Indian SMEs, further confirm that firms investing in transformation for sustainability can achieve better environmental outcomes, though these require balancing with operational and cost-related challenges. Taken together, this evidence indicates that TMI enables SMEs to build the capabilities needed for integrating sustainability into their business models, resulting in stronger EP. Therefore, we hypothesise the following:

H5: There is a positive relationship between TMI and environmental performance in SMEs.

The relationship between transformation management intensity and social performance in Small and Medium Enterprises

The social dimension of performance is increasingly influenced by how firms manage transformation processes. Kwiotkowska and Gębczyńska (2021) show that leadership, innovation orientation and sustainable transformation pathways are critical determinants of SP. Liang et al. (2022) also highlight that adaptive transformation capabilities embedded in ESG strategies contribute to improving firms’ social legitimacy and responsiveness to stakeholders. Belhadi et al. (2022) add that transformation management, through ambidexterity and circular economy models, fosters inclusive business practices and enhances firms’ ability to respond to social demands. Moreover, De et al. (2024) demonstrate that in SMEs, SP significantly enhances competitive capability, showing that transformation towards socially responsible practices is not only ethically important but also strategically valuable. Collectively, this body of work supports the argument that TMI strengthens SMEs’ ability to align with societal expectations, improve employee well-being, and foster community engagement. Thus, we hypothesise the following:

H6: There is a positive relationship between TMI and social performance in SMEs.

Conceptual framework

The conceptual framework, which incorporates DI and TMI within the RBV perspective, is based on the hypotheses formulated in the preceding section. The model illustrates how technological resources and organisational capabilities are theorised to influence financial, environmental and social outcomes in SMEs. Figure 1 presents this framework, showing the proposed relationships that guide the empirical analysis.

FIGURE 1: Conceptual framework: Impact of digital intensity and transformation management on Small and Medium Enterprises’ sustainable business performance.

The framework sets out the hypothesised relationships between the constructs and SME performance outcomes, as follows:

H1: There is a positive relationship between DI and financial performance in SMEs.

H2: There is a positive relationship between DI and environmental performance in SMEs.

H3: There is a positive relationship between DI and social performance in SMEs.

H4: There is a positive relationship between TMI and financial performance in SMEs.

H5: There is a positive relationship between TMI and environmental performance in SMEs.

H6: There is a positive relationship between TMI and social performance in SMEs.

Methodology

This study adopted a quantitative, cross-sectional research approach to examine the association between DT and sustainable business performance in SMEs. A survey approach was selected as it allows for standardised data collection and the application of statistical techniques to test hypothesised relationships. The target population consisted of SMEs operating in the City of Matlosana Municipality within North West province, South Africa. Small and Medium Enterprises owners and managers were identified as the respondents, given their role in making strategic decisions regarding digital adoption and business performance. A probability sampling strategy, precisely simple random sampling, was implemented to reduce partiality and increase representativeness. A sampling frame was compiled using publicly available SME directories and municipal local economic development business listings within the City of Matlosana. From these lists, respondents were selected using a simple random sampling approach, ensuring that each eligible SME had an equal chance of being included in the study. A total of 300 questionnaires were distributed to owners and managers of SMEs operating within the City of Matlosana Municipality. Of these, 232 were returned, representing a response rate of 71%. After screening for completeness and consistency, 213 questionnaires were considered valid and subsequently used for data analysis. This sample size was considered appropriate, as it exceeds the threshold of 200 recommended for stable multivariate statistical analysis (Hair et al., 2021). The respondents represented a wide range of business sectors, including agriculture, construction, retail and services.

Primary data was collected through a structured survey questionnaire. The questionnaire comprised three sections: Demographic information (e.g. education, firm size, years in business, sector); DT, measured through DI and transformational management intensity; and sustainable business performance, captured through financial, environmental and social indicators. The questionnaire was developed from previously validated measurement scales to improve the reliability of the data and minimise measurement bias. In addition, the survey instrument was pre-tested with a small group of SME managers to ensure that the questions were clear, relevant, and easy to understand. All items were rated on a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. Digital transformation was measured using a 20-item scale developed by He et al. (2023), while sustainable business performance was measured using a 14-item scale adapted from Jabbour et al. (2020) and Huo et al. (2019).

Ethical considerations

Ethical clearance to conduct this study was obtained from the University of Johannesburg and the Johannesburg Business School Research Ethics Committee (No. JBSREC2024223). All respondents gave their informed consent, and participation was entirely voluntary. Confidentiality and anonymity were guaranteed, and the data were used solely for academic purposes.

Results

Respondents’ profile

The analysis of educational levels among respondents revealed that most individuals (51.6%) reported that high school was their highest level of education. Followed by 25.8% who had obtained a diploma qualification. A smaller portion of the sample, 12.2%, held an undergraduate degree, while only 10.3% had completed postgraduate studies. These statistics indicate a workforce that is primarily composed of individuals with basic to intermediate educational qualifications. Regarding the size of businesses represented in the study, an overwhelming 80.7% of enterprises reported employing fewer than five people. An additional 19.2% employed fewer than 20 people, while no respondents indicated having businesses that employed 50 or more individuals. This skew towards micro-enterprises reflects a characteristic trend in many emerging economies where entrepreneurship is often necessity-driven and concentrated in the informal or semi-formal sector. When considering the duration of business operation, the data indicated a relatively even distribution across experience levels. Approximately 18.3% of the businesses had been operational for less than 1 year, and 23.9% had been in existence for 1–2 years. A slightly higher proportion (24.8%) had operated for 3–4 years, while the largest group (32.8%) reported business operations extending beyond 5 years. This distribution suggests a vibrant entrepreneurial environment with a healthy mix of both new entrants and more seasoned operators. However, the significant number of businesses in their early stages may also imply potential volatility and higher business failure rates, necessitating tailored support mechanisms to enhance sustainability and long-term success. The sectoral distribution of respondents highlighted a predominance of service-oriented and primary sector activities. The highest representation was found in the community, Social and Personal Services, comprising 17.3% of the sample. This was closely followed by Agriculture and Catering, Accommodation and Other Trade sectors, each contributing 15.4%. Retail and Motor Trade and Repair Services accounted for 12.2%, while construction followed at 11.7%. Other notable but less represented sectors included Finance and Business Services (11.2%) and Transport, Storage and Communications (4.6%). In contrast, capital-intensive and heavily regulated sectors such as Mining and Quarrying (2.8%) and Electricity, Gas and Water (1.4%) were minimally represented. This trend suggests a local economy driven largely by accessible and lower-barrier sectors, which typically require modest capital investment and offer quicker entry. These sectors often absorb a significant portion of informal or semi-formal labour, reflecting the structural composition of entrepreneurship in the region. Table 1 illustrates the demographic characteristics.

Reliability and validity tests in confirmatory factor analysis

In structural equation modelling (SEM) frameworks, reliability analysis is a critical component of ensuring that measurement instruments are consistent with one another. The study’s reliability was assessed using Cronbach’s Alpha (α) and Composite Reliability (CR or ρc). Table 2 illustrates the results. These are two frequently recommended metrics for reflective measurement models (Hair et al., 2021; Taber, 2018).

Table 2 shows that all five latent components in the investigation had high internal consistency. The figures for Cronbach’s alpha increased from 0.911 for FP to 0.968 for SP. The CR values increased from 0.933 to 0.975. Awang et al. (2018) and Purwanto and Sudargini (2021) demonstrate that the measurement model is robust, as the reliability threshold of 0.70 for both indices is substantially lower than these figures. Digital Intensity was a dependable method for evaluating DT abilities, as evidenced by its α value of 0.960 and CR value of 0.965. The reliability of the EP and FP constructs was demonstrated by their α values of 0.930 and 0.911, respectively, and their CRs of 0.950 and 0.933. The most reliable values were achieved by TMI and SP (α = 0.967 and 0.968, respectively). These values may indicate that the model is accurate; however, they may also indicate that certain items require verification for redundancy (Henseler et al., 2016; Nunnally & Bernstein, 1994).

Convergent validity assessment

Table 3 shows the assessment for convergent validity. Fornell and Larcker (1981) assert that Average Variance Extracted (AVE) values should exceed 0.50 to demonstrate that the latent construct, rather than error, accounts for more than 50% of the variance in the indicators. In addition, standardised factor loadings should exceed 0.70; however, loadings between 0.60 and 0.70 may be acceptable for exploratory research (Henseler et al., 2016; Saeed et al., 2022). The item’s high factor loadings indicate that it has a significant amount of variance in relation to the construct it is intended to evaluate.

Table 3 demonstrates that the AVE values of all five components exceed 0.736, which is significantly higher than the standard 0.50 threshold. This demonstrates that the measurement model has a high degree of convergent validity. The AVE of DI is 0.736, with factor loadings ranging from 0.802 to 0.906. This indicates that DI is internally consistent. Environmental Performance exhibited an even higher AVE of 0.826, with loadings ranging from 0.900 to 0.925, which further enhanced the construct’s coherence. The FP score was 0.736, which was equivalent to the criterion. The construct’s validity was confirmed by loadings such as 0.891. The item loadings were greater than 0.940, which contributed to the highest AVE of 0.888 for SP. This demonstrates that the items are highly comparable; however, it also raises concerns about their potential redundancy. The TMI also achieved an AVE of 0.774, with loadings ranging from 0.815 to 0.924, indicating its reliability.

Discriminant validity assessment

In this study, the Heterotrait-Monotrait Ratio (HTMT) and the Fornell and Larcker Criterion were two widely recognised methods for evaluating discriminant validity.

Fornell and Larcker criterion

The Fornell and Larcker criterion is a traditional method for evaluating discriminant validity. According to Fornell and Larcker (1981), the square root of the AVE of a construct should be greater than its correlation with any other construct in the model. This criterion guarantees that the construct’s variance with its own indicators is greater than that of other constructs.

The Fornell and Larcker criterion is employed in Table 4 to compare the correlations between constructs in the off-diagonal cells with the square roots of AVEs on the diagonal. The findings indicate that discriminant validity is present in all constructs. For example, the square root of the AVE for DI is 0.858, which is greater than its associations with EP (0.740), FP (0.734), SP (0.753) and TMI (0.845). The square root AVE of EP is 0.909, which is greater than its correlations with FP (0.861), SP (0.855) and TMI (0.614). The discriminant efficacy of SP is further enhanced by its highest diagonal value of 0.942.

Heterotrait-Monotrait ratio

The HTMT Ratio results, as illustrated in Table 5, indicate that all inter-construct values are below the conservative criterion of 0.90. The relationships between EP and FP (0.925), EP and DI (0.780), SP and FP (0.825) and TMI and DI (0.873) are among the examples. The HTMT score between EP and FP is just above the cautious 0.90 threshold, but it remains below the strict requirement of 1.0. These findings demonstrate that, despite their interconnections, the constructs are sufficiently distinct in the real world to be treated as distinct theoretical entities within the model.

Measurement model accuracy statistics summary

Means and standard deviations were examined as scale statistics. The standard deviations were less than 1.4, and most of the mean values fell within the range of 2.7 to 3.3. This implies that the respondents primarily concurred, and there was minimal variation. The indicators employed in the model are corroborated by these figures.

Path modelling

Path modelling illustrates the relationship between seen or measured variables and a theoretical construct, in addition to examining the structural courses of a hypothesised research model (Guenther et al., 2023). To assess the effectiveness of the study’s structural model, p-values and regression coefficients were both examined. Figure 2 illustrates one potential result of the structural model for the theory that is being presented.

FIGURE 2: Structural model.

The measurement and structural model evaluations’ overall findings support the validity and reliability of the constructs employed in this investigation. All indicators met or exceeded the recommended thresholds for internal consistency, convergent validity and discriminant validity, while model fit indices indicated an acceptable level of fit. These results provide confidence that the measurement model is robust and suitable for testing the proposed research hypotheses.

Hypothesis testing

With the validity and reliability of the measurement model established, the next stage of the analysis involved testing the hypothesised relationships between DT (DI and transformational management intensity) and sustainable business performance (financial, environmental and social dimensions). The hypothesis testing results for this study’s estimation are presented in Table 7. The table displays the path coefficients, the t-statistics, the proposed hypothesis and whether the hypothesis is supported or rejected. Path coefficients greater than one indicate a strong relationship between latent variables, while t > 1.96 indicates a robust association (Zhang, 2022):

H1: There is a positive relationship between DI and FP.

The structural model results show that FP is significantly and positively influenced by DI, with a t-statistic of 7.533, a path coefficient (β) of 0.762 and a p-value of 0.000. This indicates that SMEs with higher DI achieve stronger financial outcomes. In practice, firms that allocate substantial resources to digital technologies, systems and capabilities are more likely to experience cost efficiencies, revenue growth and financial resilience. These results provide support for Hypothesis 1 (H1) and are consistent with prior studies. Moro-Visconti et al. (2025) highlight how digital platforms improve revenue streams, reduce costs and enhance financial viability. Criveanu (2023) similarly finds that DI contributes to competitiveness and economic performance, while Nasiri et al. (2022) emphasise the role of DI in enabling adaptability and long-term financial advantage. More recent applied studies also reinforce this link, showing how digital investments reduce transaction costs and enhance decision-making efficiency (Bindeeba et al., 2025; Gertzen et al., 2022):

H2: There is a positive relationship between DI and environmental performance.

The structural model results show that EP is significantly and positively influenced by DI, with a path coefficient of β = 0.777, a t-statistic of 7.389 and a p-value of 0.000. This indicates that higher levels of DI enable SMEs to achieve stronger environmental outcomes. In practice, firms that embed digital technologies into their operations are better able to optimise resource use, reduce waste, and adopt greener practices.

These results provide support for Hypothesis 2 (H2) and align with prior studies. Zhang and Zhao (2023) demonstrate that DI enhances firms’ capacity to improve EP by integrating sustainability goals with digital processes. Table 6 illustrates the scale accuracy analysis of the measurement items. Similarly, Chen and Ren (2025) find that DT significantly contributes to ESG outcomes, with particularly strong effects on environmental dimensions. Burinskienė and Nalivaikė (2024) further argue that SMEs adopting digital solutions are better positioned to meet sustainability objectives, particularly in the context of the EU Green Deal:

H3: There is a positive relationship between DI and SP.

The structural path analysis indicates a statistically significant and robust correlation between DI and SP. This is demonstrated by a route coefficient of β = 0.616, t = 6.258 and p = 0.000. This is consistent with Hypothesis 3, which posits that companies’ SP, as measured by ethical governance, community involvement and stakeholder engagement, improves when they exert more effort to become digital. However, the correlation is not as robust as DI’s influence on environmental and FP. This implies that the social advantages of DT may be contingent upon the circumstances or may accrue gradually. The results of hypothesis 3 support Meng et al. (2022) finding that enhanced DI improves SP:

H4: There is a positive relationship between TMI and FP.

The results of the structural model for H4 indicate that there is no significant correlation between FP and TMI, with a path coefficient of β = –0.033, a t-value of 0.282 and a p-value of 0.778. This suggests that, within the SME context, TMI has little to no direct impact on financial outcomes. As a result, Hypothesis 4 (H4) is not supported. This finding contrasts with prior research, which generally identifies a positive relationship between transformation management and FP. For example, Mwangi and Mang’ana (2024) show that dynamic managerial capabilities strengthen financial outcomes in logistics firms, while Liang et al. (2022) argue that adaptive capabilities embedded in transformation strategies generate long-term financial advantage. Belhadi et al. (2022) also find that transformation initiatives integrating Industry 4.0 practices improve operational efficiency and economic resilience. The SME context may be the reason for the discrepancy between these studies and the current findings. Unlike larger firms, SMEs often face resource constraints and shorter planning horizons, which may limit the translation of transformation management efforts into immediate financial returns:

H5: There is a positive relationship between TMI and EP.

The structural model demonstrated a statistically insignificant and weak negative correlation between TMI and EP, with a path coefficient of β = −0.043, a t-value of 0.335, and a p-value of 0.715. These results indicate that TMI does not significantly influence EP in the context examined. Consequently, Hypothesis 5 (H5) is not supported. This finding contrasts with much of the literature, which suggests that transformation management can enhance environmental outcomes. Studies such as Wang and Teng (2022) and Yu and Ramanathan (2016) emphasise that managerial capabilities strengthen supply chain and operational practices that improve EP, while Belhadi et al. (2022) show that Industry 4.0 transformation fosters circular economy models that support emissions reduction and sustainable resource use. However, the present results are consistent with Kargas et al. (2024), who argue that transformation effort or management intensity alone is insufficient to produce meaningful environmental improvements:

H6: There is a positive relationship between TMI and SP.

Although the hypothesis proposed a positive relationship between TMI and SP, the statistical results do not support this claim. The path coefficient (β = 0.162) suggests a slight positive trend; however, the t-value (1.485) and p-value (0.138) fall below the commonly accepted thresholds for significance (t ≥ 1.96; p < 0.05). These results indicate that TMI does not have a statistically significant impact on SP in the context examined. Consequently, Hypothesis 6 (H6) is not supported. This finding diverges from prior literature, which has emphasised the social benefits of transformation management. For example, Kwiotkowska and Gębczyńska (2021) highlight the importance of leadership and sustainable transformation pathways in improving social outcomes, while Belhadi et al. (2022) suggest that transformation efforts can foster inclusive practices through circular economy models. However, the present results align with Chen and Wang (2024), who argue that improvements in ESG performance are significantly mediated by factors such as innovation capability and service orientation, rather than being directly attributable to transformation intensity alone.

Discussion

These results suggest that, for SMEs, transformation management may not be sufficient in isolation to generate measurable social benefits. Instead, complementary capabilities such as innovation and stakeholder engagement may be necessary to convert transformation efforts into meaningful SP outcomes. In general, while the findings indicate that DI consistently drives financial, environmental and SP, TMI did not emerge as a significant predictor in this study. This has important implications for understanding DT for Sustainable Business Performance in SMEs within the South African context. From an RBV perspective, sustainable competitive advantage arises when firms mobilise both technological resources and organisational capabilities (Barney, 1991; Wernerfelt, 1984). Digital intensity, as a technological resource, appears to directly enhance efficiency, innovation, and responsiveness, which in turn supports the triple bottom line. By contrast, the results show that TMI, as an organisational capability, may only yield results when paired with sufficient technological foundations.

The South African SME environment helps to explain this divergence. Many SMEs operate with limited managerial and strategic capacity, meaning that even strong leadership commitment to transformation does not automatically translate into measurable performance gains. In resource-constrained contexts, the adoption of digital tools, such as cloud systems, mobile payments and e-commerce, produces immediate and visible benefits for financial and operational outcomes (Criveanu, 2023; Nasiri et al., 2022). Additionally, SMEs in South Africa face short-term survival imperatives and structural barriers that weaken the translation of TMI into results. Persistent skills shortages, high data costs and unreliable infrastructure constrain the ability of managers to sustain transformation initiatives (Omowole et al., 2024). These findings align with broader evidence that SMEs often remain at the margins of DT, unable to progress beyond piecemeal adoption (Masood & Sonntag, 2020). In RBV terms, while TMI represents an important intangible capability, its value can only be realised when supported by robust digital resources and a conducive ecosystem (Aqmala et al., 2025).

The findings of this study should be considered within the broader context of the realities faced by small businesses in South Africa. While DT has the potential to improve efficiency, foster innovation and promote more sustainable business performance, these benefits are not always fully achieved in practice. Small and medium-sized enterprises often encounter practical challenges that limit their ability to adopt digital technologies effectively. In the South African context, studies have shown that many SMEs face constraints such as limited access to reliable internet connectivity, inadequate digital infrastructure, low levels of digital awareness and resistance to organisational change. These challenges make it difficult for small businesses to integrate digital tools into their everyday operations and participate fully in increasingly digitalised supply chains.

As a result, although DT can play a significant role in enhancing sustainable business performance, its overall impact is strongly influenced by the contextual conditions present in emerging economies like South Africa. Addressing gaps in infrastructure, strengthening digital skills development, improving access to financial resources and establishing supportive policy frameworks are, therefore, critical steps in enabling SMEs to fully benefit from DT and achieve long-term sustainable performance.

Implications

This study advances the RBV by showing that digital resources are essential enablers of sustainable competitiveness in SMEs and extends sustainability research by highlighting the financial, environmental and social benefits of DT. For practice, SME leaders should prioritise investment in digital platforms, analytics and automation to strengthen DI, while support agencies must provide funding, training and advisory services to enhance SMEs’ digital capabilities. Embedding triple bottom line objectives into digital strategies is vital to ensure integrated and sustainable outcomes.

For policymakers and institutions that support SMEs, the findings emphasise the need to strengthen the wider digital ecosystem that enables SME transformation. This could involve expanding programmes that develop digital leadership and skills, providing financial incentives or grants to encourage technology adoption, and improving access to reliable digital infrastructure. Policymakers could therefore enhance these efforts by introducing sustainability-linked incentives, such as funding programmes or tax benefits that motivate SMEs to align digital adoption with environmental and social goals. In addition, support agencies could encourage SMEs to use organisational readiness or culture assessment tools to evaluate their preparedness for DT and identify capability gaps. Collectively, these measures can assist SMEs in turning DT initiatives into tangible improvements in financial, environmental and SP.

Limitations and future research

This study is limited by its focus on SMEs within a single municipality, its cross-sectional design, reliance on self-reported data, and the predominance of service-oriented firms in the sample, which constrain generalisability and causal inference. Future research should adopt longitudinal or mixed methods approaches, expand samples across regions and sectors, and include under-represented industries such as manufacturing and high-tech. Further studies could also explore mediating and moderating factors, such as innovation capability, leadership style, government support, digital literacy and cultural influences, in shaping the DT–sustainability relationship.

Conclusion

The aim of this study was to examine, through the lens of the RBV, how DT shapes sustainable business performance in South African SMEs by distinguishing the roles of DI and TMI. The results show that DI is positively and significantly associated with financial, environmental and SP, whereas TMI does not exhibit a statistically significant effect on any dimension. Viewed through RBV, these findings suggest an asymmetry in the resource–capability configuration: Technological resources (DI) provide the necessary base for performance gains, while organisational capabilities (TMI) contribute only when anchored in a sufficiently developed digital infrastructure. Practically, SMEs and supporting institutions should prioritise affordable digital infrastructure and skills development as the foundation, followed by targeted capability building to convert DI into durable advantages.

Acknowledgements

The authors extend their sincere appreciation to the SMEs for their valuable participation in this study.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

CRediT authorship contribution

Ralebitso Kenneth Letshaba: Conceptualisation, Formal analysis, Investigation, Methodology, Writing-original draft, Lebogang T. Mosupye-Semenya: Data curation, Validation, Visualisation, Writing-original draft. Both authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication and take responsibility for the integrity of its findings.

Funding information

The authors received no financial support for the research, authorship and/or publication of this article.

Data availability

The data that support the findings of this study are not openly available and are available from the corresponding author, Ralebitso K. Letshaba, upon reasonable request.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings, and content.

References