Digital marketing and small and medium-sized enterprises’ business performance in emerging markets

Abstract

Purpose

This study aims to investigate the comprehensive conceptualization how digital marketing and its adoption increase the productivity of small and medium-sized enterprises (SMEs), as well as the impact of technological orientation, customer relationship management and digital marketing on SMEs’ business performance in emerging markets (EMs).

Design/methodology/approach

Anchored by social network theory, 178 SMEs were conveniently drawn from the National Board for Small Scale Industries now Ghana enterprise agencies in Ghana. The hypotheses were analysed using the SPSS package tool, and structural equation modelling was used, as well.

Findings

This study reveals that the conceptualization and adoption of digital marketing positively affect the performance of SMEs’ business management in EMs. In addition, a positive moderating effect of dynamism is observed in the relationship between digital marketing and SMEs’ business performance.

Research limitations/implications

This study focuses only on SMEs from the Greater Accra and Ashanti regions of Ghana as an EM, and it proposes priorities for future research streams in both developed and emerging countries.

Practical implications

The findings encourage SMEs to develop quality digital marketing technologies, good customer relationships and technological orientation and customer relationship management competencies in EMs to maximise profit.

Originality/value

This paper fills considerable knowledge, evidence and contextual gaps in the literature on SMEs, entrepreneurship and marketing in EMs by presenting a comprehensive overview of how SMEs can use digital marketing in an EM context to achieve the following: customer acquisitions, satisfaction and retention; increased profitability; quality service delivery; value creation; and cost reductions.

Citation

Deku, W.A., Wang, J. and Preko, A.K. (2024), "Digital marketing and small and medium-sized enterprises’ business performance in emerging markets", Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 18 No. 3, pp. 251-269. https://doi.org/10.1108/APJIE-07-2022-0069

1. Introduction

In emerging markets (EMs), small and medium-sized enterprises (SMEs) can look forward to modern marketing tools, known as digital marketing technologies (DMTs), including search engines, email and social media marketing, to take advantage of unique business opportunities and to achieve a competitive advantage. Global conceptualisations and commercialisation’s of DMTs at this time have become the backbone of inter-organisational and customer-centric SMEs’ business processes in EMs (Amelda et al., 2021; Al Asheq et al., 2021; Chinakidzwa and Phiri, 2020; Cheng and Shiu, 2019; Olusegun et al., 2020).

Currently, around the world, DMTs have changed the operations of SMEs and the understanding of marketing communication in EMs (Foltean et al., 2019, p. 563; Chong et al., 2018). In developed countries, DMTs bring new market opportunities through globalisation of force, which helps SMEs in designing their business operations and processes in a dynamic environment (Harrigan et al., 2020; Wang, 2020, p. 559). In EMs, DMTs aid in understanding customers’ needs and wants, as well as SMEs’ business performance (Durukal, 2021, p. 82; Hernández-Linares et al., 2021). In Africa, DMTs are seen as strategic tools for SMEs in EMs to achieve high profits (Huang and Chen, 2018, p. 639). In Ghana, Deku et al.(2022) argued that DMT conceptualization and adoption of digital marketing positively affect the performance of SMEs’ business management in EMs. Deku et al. (2022) discovered that DMT has a positive moderating effect on dynamism in the relationship between digital marketing and SMEs’ business performance.

In Ghana, SMEs that adopt and commercialise DMTs face such challenges as financial constraints, low market activity, low technology adoption and poor managerial skills (Jean and Kim, 2019; Yousaf et al., 2018, p. 313). These challenges create an extant knowledge gap necessitating further research into DMTs and performance in EMs (Liu et al., 2020; Wang, 2020, p. 559).

Despite the proliferation of research on SMEs performance on entrepreneurship globally, little is known about the relationship between SMEs business performance, digital marketing capabilities (DMCs) and DMTs: search engine marketing, social media marketing adoptions, applicability and implementations in EMs. Therefore, the scant adoption, applicability and implementation of DMCs and DMTs in EM SMEs has created extant contextual, knowledge and evidence research gaps in entrepreneurship and marketing literature (Deku et al., 2022, 2021). To fill these gaps in EM, DMCs model has being incorporated which was first created to overcome the marketing challenges faced by SMEs in Ems. Secondly, the appropriateness applications of DMTs perspective to explain SMEs performance has been explored. By placing DMTs within the context of a broader strategy, a model was created in which dynamism and competition intensity are suggested to mediate the impact of DMTs on SMEs’ performance in EMs. The purpose of this study is to establish a comprehensive relationship between DMTs applicability and SMEs’ business performance in EMs, and its objective is to examine the impact of DMTs applicability on SMEs’ business performance according to the following variables: profit, efficiency and growth, as well as customer acquisitions and retentions in the EMs context. The aim is to examine the impact of businesses’ customer relationship orientation, technological orientation and competence of social customer relations management (CRM) on DMTs.

2. Theory development and literature review

2.1 The applicability of social network theory in emerging markets

Social network theory (SNT) is a valuable tool that considers how technological investment relates to the strategic value of information technology (IT) based on different attributes of resources and business performance capabilities in EMs (Liu et al., 2017). This study gives significant exposure to SME business policymakers and implementers, including governments, entrepreneurs and owners/managers, concerning how DMTs have changed the scope of SMEs’ business and the facilitation of two-way communication and the profit maximisation of SMEs’ success in Ems.

This study contributes to the marketing and entrepreneurship literature by bridging the evidence, contextual and knowledge gaps between DMTs and SMEs’ business performance in EMs, as well as to how SMEs can improve their operational policies, value creation and customer satisfaction in EMs. The structure of the study is as follows. Section 2 reviews the literature on theory, digital marketing and SMEs’ performance and Section 3 presents the methodology. Section 4 includes the data analysis and results, whereas Section 5 offers conclusions, managerial implications and avenues for future study.

2.2 Theory grounding the study: social network theory

This research is grounded in SNT, which was introduced in the 1890 s in the study of the structure of society and business. SNT was popularised by Jacob Moreno in the 1930s in EMs (Liu et al., 2017) and mathematically formalised in the 1950s to study interpersonal relationships among SMEs in EMs. SNT is a theoretical model that emphasises the importance of social relations for business in EMs, a complex, interdisciplinary field that draws from sociology and psychology (Liu et al., 2017). SNT in EMs suggests that social actors are influenced by the personal ties of other people in their personal networks (Liu et al., 2017). Through SNT, DMTs have been studied and established as social relationships in the form of nodes and ties for SME success in EMs (Olusegun et al., 2020).

Olusegun et al. (2020) discovered that SNT offers value to SME owners/managers by contributing social resources that are entrenched within a network of DMTs for SMEs in EMs. As validated by researchers (Olusegun et al., 2020), digital marketing platforms are characterised by network effects, such as desktops and network switches, to increase the demand and supply of SMEs in EMs (Olusegun et al., 2020), and SNT is used to argue that digital marketing on social networking platforms, such as Twitter, LinkedIn and Facebook, is renowned for improving SMEs’ performance in EMs. Olusegun et al. (2020) further used SNT to argue that digital marketing has changed the communications strategies used by entrepreneurs to achieve success in EMs. To address the challenges related to knowledge and evidence gaps and to understand the application and practice of SNT in the marketing, management and entrepreneurship fields, DMTs were conceptualised in the Ghanaian context as added value for customers, customer satisfaction and quality service delivery in EMs as the building blocks of this study.

2.3 Literature review and hypotheses

2.3.1 Digital marketing capabilities in emerging markets.

Digital marketing in EMs refers to the use of electronic information and communication technologies, especially the internet, to achieve marketing targets profitably (Wang, 2020; Liu et al., 2020; Herhausen et al., 2020). It includes the use of the internet and other interactive technologies to create and mediate dialogue between SMEs and their identified customers in EMs. The primary advantages of digital marketing in EMs are reduced costs, increased customer access and increased business performance.

Digital marketing makes it easier for SMEs to develop creative ideas that will help them design innovative products in EMs and to improve their performance (Utomo and Susanta, 2020; Wang, 2020; Liu et al., 2020; Herhausen et al., 2020).

Table 1 studies on the digital marketing capability in EM, digital marketing technologies, SMEs’ business performance and customer relationship management. They argue their paper fills considerable knowledge, evidence and contextual gaps in the literature on SMEs, entrepreneurship and marketing in EMs by presenting a comprehensive overview of how SMEs can use digital marketing in an EM context to achieve the following: customer acquisitions, satisfaction and retention; increased profitability; quality service delivery; value creation; and cost reductions. Table 2 by authors. Number of employees, business models and digital marketing activities in EM. Figure 2 by the authors: Model constructs on customer relations orientations. Table 3 by authors: SEM Analysis on customer relation orientation, social CRM competence, technology orientation, digital marketing capabilities, market environment, market environment dynamism, market environment competition intensity and business performance (note: Kaiser–Meyer–Olkin (KMO) = 0.912/Bartlett test of sphericity: Chi-square value: 5,924.490 p = 0.000. Explained variance: 72.896%). Table 4 by the authors. The goodness of fit indexes and structural model of the research model. Table 5 by the authors. Results of the research model. Table 6 by the authors: Descriptive statistics for computed variables. Conceptual frame work I: by the on authors customer relation orientation, social CRM competence, technology orientation, digital marketing capabilities, market environment, market environment dynamism, market environment competition intensity and business performance. Table 8 by authors conducted a researched on customer relationship orientations, social CRM competitions, technology competitions, digital marketing capabilities, business performance and market environment they discovered a positive impact relations on SMEs performance in an EM significant at the 0.05 level.

DMCs in EMs help SMEs improve their performance by enabling knowledge of market and customer information on prices, services quality, customer acquisitions, brand promotion, customer retainment and increased sales (Pour and Hosseinzadeh, 2020; Amelda et al., 2021, p. 14; Utomo and Susanta, 2020, p. 167).

Anchored on SNT, 178 SMEs were conveniently drawn from the National Board for Small Scale Industries now Ghana enterprise agencies in Ghana. They discovered that DMCs have positive and significant effects on SMEs business performance in Ghana as an EM. Amelda et al. (2021), in their study of 100 bank employees in Indonesia, examined the impact of digital technology, digital leadership and digital marketing on business performance. They concluded that DMCs have a positive and insignificant effect on SMEs’ business performance in EMs (Figure 1). LISREL, structural equation modelling (SEM), confirmatory factor analysis (CFA), Kaiser–Meyer–Olkin (KMO) test, root mean square error of approximation (RMSEA), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), non-normed fit index (NNFI), comparative fit index (CFI), root mean square residual (RMR), standardised root mean square residual (SRMR) and average variance extracted (AVE) were used to study digital marketing and SMEs’ business performance in EMs – EMs, digital marketing technologies, SMEs’ business performance and customer relationship management. They argued that DMC have a positive impact on SME performance in EM.

Furthermore, Herhausen et al. (2020) systematically examined 129 articles covering 20 years of research to determine DMCs from a resource-based perspective: channels, social media, digital relationships and digital technologies. They argue that DMCs have a positive impact on SMEs’ performance. Furthermore, Liu et al. (2020) explored how DMCs affected the international market performance of 132 companies in Taiwan of China, and they discovered that DMCs have a significant impact on SMEs’ performance in EMs. Table 1 lists some studies in the literature on DMCs in EMs. Table 8 researched on customer relations orientation, social CRM competence, technology orientation, digital marketing capability, business performance and market environment on overall SME performance. It was revealed they have positive impacts on overall SMEs performance in an EM.

2.3.2 Customer relation orientation in emerging markets.

Customer relation orientation in EMs is an important perspective of SMEs and is considered a capability that enables SMEs to develop behaviours that will aid in understanding customers, enabling SMEs to improve their performance (Trif et al., 2019). In today’s competitive business environment, the performance of SMEs in EMs increasingly depends on SMEs’ ability to operate CRM, which will enable the development and implementation of efficient and effective customer-focused strategies. Although SMEs in EMs have made enormous investments in CRM technology, empirical research provides inconsistent evidence that CRM technology improves organizational performance, leading to extant knowledge gaps.

Mohammed conducted research on the relationship between CRM technology and organisational performance, arguing that there is no statistically significant relationship between CRM and SMEs’ performance in EMs. These mixed results are thought due to a lack of understanding of the mechanisms linking CRM technology with SMEs’ performance in EMs (Trif et al., 2019). Despite the strong conceptual relationship, more research is needed to examine the role of mediating and contingent variables, as previous studies by Al Asheq et al. (2021), Rupeika-Apoga et al. (2022) and Pan et al. (2021) investigated the direct relationship between CRM and SMEs’ performance and produced conflicting results, stating that CRM technology has no effect on SMEs’ performance.

To bridge this knowledge and evidence gap, marketing capabilities (planning and implementation) are used as intermediaries between CRM technology and SMEs’ performance in EMs. Used marketing capabilities (planning and implementation) in EMs as a mediator between CRM technology and business performance in a study conducted at 447 hotels in Malaysia, revealing that marketing capabilities (planning and implementation) do not play a mediating role in the relationship between CRM technology and various dimensions of business performance. Therefore, does the adoption of marketing capabilities (planning and implementation) by SMEs aid them in developing good DMCs to respond to their customers effectively? To answer this question, the following hypothesis is proposed:

H1.

Customer relationship orientation in SMEs is positively related to DMCs in EMs.

2.3.3 Social customer relationship management competence in emerging markets.

The development of CRM competency in EMs has significantly increased the use of social media and the number of social networks in EMs, such as Facebook, Twitter and Google, to help SMEs improve their performance (Harrigan et al., 2020). CRM competency with social media in EMs has become an integral part of modern society, improving SMEs’ performance. Therefore, today’s marketers must find ways to keep up with the flow of data that comes to them through myriad channels in EMs. Modern SMEs that want to improve their performance must follow and understand what is said about them, their products and their competitors via user-generated content and social media channels, as well as establish and manage their social media sites in EMs (Kim and Wang, 2019, p. 42).

Social media in EMs is a necessity for SMEs to remain competitive in the market, functioning as a tool to manage and strengthen relationships with customers to improve performance. However, it can facilitate value creation and knowledge sharing in EMs (Pour and Hosseinzadeh, 2020, p. 43). Previous studies of IT competency have proven that it can have a positive impact on IT capabilities and performance (Al Asheq et al., 2021; Bamfo and Kraa, 2019; Rupeika-Apoga et al., 2022).

SMEs that have a high level of social CRM competence tend to use social media better than other SMEs because social media belongs to IT in EMs. Because all media belong to IT, SMEs with social media CRM skills tend to perform better than other companies that do not have these skills. There are challenges with successfully implementing social CRM in EMs because of the processes and capabilities. To fill these knowledge and evidence gaps in the entrepreneurship and marketing literature, this study reviews the literature on social CRM to identify the capabilities that SMEs in EMs must possess to implement social CRM strategies effectively to improve their performance (Diffley et al., 2018, p. 1074). Therefore, in line with this information, the following hypothesis is suggested:

H2.

Social CRM competence in SMEs is positively related to DMCs in EMs.

2.3.4 Technology orientation in emerging markets.

Technology orientation in EMs, also referred to as innovation orientation, states that SMEs can achieve sustainable success and performance in EMs using new technological processes, products and services. Just as customer orientation is important to improving the performance of SMEs in EMs, technological orientation in EMs must be studied as well if SMEs in EMs want to improve their performance. To remain dynamic in the market environment in EMs and to cope with competition intensity, technological innovations must be adopted quickly by SMEs if they want to improve their performance.

Depending on the intensity of the competition facing SMEs in the EM environment, technological orientation is recommended as a critical strategic option for SMEs to maintain competition if they want to improve their performance. Al Asheq et al. (2021) examined the impact of e-marketing orientation, technological orientation and learning capability on SMEs’ performance in Bangladesh, arguing that e-marketing orientation, technology orientation and learning capability have a statistical and significant impact on SMEs’ performance. Pan et al. (2021) explored the role of strategic technological and customer orientation in promoting firms’ digital capabilities, finding that technological orientation and customer orientation both play a critical role in driving firms’ digital capabilities. They further argue that the two dimensions of strategic orientation tend to exert different effects on performance.

Rupeika-Apoga et al. (2022) explored the effect of digital orientation and digital capability, as well as the mediating effect of digital capabilities on SMEs during the COVID-19 pandemic. They discovered that digital orientation and digital capabilities have direct positive effects on SMEs, and they found that digital transformation has a positive mediating effect from digital orientation on SMEs. There is scant literature on technological orientations in EMs, leading to knowledge and evidence gaps. To fill them, the following hypothesis is proposed in this study:

H3.

The technological orientation in SMEs is positively related to DMCs in EMs.

2.3.5 Business performance in emerging markets.

Previous studies are still inadequate in understanding the relationship between SMEs’ abilities and performance in EMs. While some SMEs in EMs use their capabilities successfully, others are unable to use them to improve their performance, meaning the success of an SME alone is not enough to adopt digital technology for the company’s business processes in an EM (Amelda et al., 2021, p. 14).

SMEs in EMs that focus on DMCs have attached importance to customer value to improve their performance (Deku et al., 2021). In addition, for SMEs that want to improve their performance in EMs, marketing capabilities are crucial to achieve a competitive advantage. Some studies focused on the relationship between marketing ability and performance to guide SMEs and found a positive relationship between the two (Feng et al., 2017).

Furthermore, Mathews et al. (2016) and Qureshi et al. (2017) examined the relationship between marketing capabilities and market performance, finding it to be negative. As well, the research of Amelda et al. (2021) and Deku et al. (2022) on DMCs in EMs identified a positive impact on SMEs’ performance.

Bagodi et al. (2021) studied the performance measures and quality management systems (QMSs) in SMEs in India, and they found that the employee dimension is crucial to ensuring effectiveness, customer satisfaction and solid finances among SMEs. Their studies further discovered that customer satisfaction results from employee satisfaction and processes in SMEs. They again argued that a QMS impacts processes, whereas employee performance establishes the causality between business performance factors and QMSs in SMEs. Their research found that a QMS impacts finances in the short term but yields long-term benefits and is dependent on two factors: degree of knowledge of quality practices and its application in SMEs. Finally, they suggested a shift from traditional approaches, correcting defects using statistical quality control approaches towards a sustainable growth path, a long-term approach among SMEs. Sreenath and Bagodi (2017) conducted research on the interrelationships among performance measures towards excellence in SMEs, and they argued that SMEs are vital in a modern economy to gain a competitive advantage.

They (Sreenath and Bagodi, 2017) discovered that financial indicators are often considered a measure of health in SMEs, and they found that employee, process and customer indicators affect financial indicators in SMEs and that employee indicators affect process indicators and process indicators affect customer indicators in SMEs. However, empirical research is still highly limited in understanding the relationship between DMCs and performance in EMs, which creates knowledge and evidence gaps. Therefore, the following hypothesis is proposed in this study:

H4.

DMCs are positively related to SMEs’ business performance in EMs.

2.3.6 Market environment in emerging markets.

Continuous monitoring and classification of the market environment in EMs is important to market orientation to improve SMEs’ performance (Halliru, 2016). It is also crucial for SMEs to discover new market opportunities for the right target audience, as well as to design and produce goods and services that meet the needs of the target audience and protect the market environment in which SMEs operate in EMs.

To compete in the market environment, SMEs must switch to a dynamic application in EMs. The shortening of the product lifecycle, rapid changes in customer demands and rapid increases in the intensity of competition in EMs make it necessary to keep up with the dynamic market conditions, as SMEs in EMs that have a dynamic structure – in consideration of the dynamism and competition intensity in the market environment – can adapt more easily to changing situations, achieving higher satisfaction and improving performance.

If SMEs in EMs want to improve their performance, they must implement market environment factors, such as dynamism, competition intensity and strategies that will activate their DMCs. The dynamism and intensity of competition, used to explain the market environment, are a driving force for growth and add quantitative and qualitative diversity to the market environment in EMs. Therefore, SMEs in EMs must increase their dynamic market practices to remain competitive and improve their performance in the market environment. Bamfo and Kraa (2019) assessed the impact of market orientation on the performance of SMEs, as well as the mediating role of innovation, arguing that the market orientation variable of customer orientation positively and significantly affects the performance of SMEs in Ghana. Wardaya et al. (2019) conducted a study on the mediating effects of digital marketing on dynamic capability and firm performance in Indonesia, and they found that dynamic capability has a positive direct influence on DMCs and SMEs’ performance. Therefore, the following hypothesis is proposed in this study:

H5.

Dynamism has a positive moderating effect (mediation role) on the impact of DMCs on SMEs’ performance in EMs.

2.3.7 Marketing capabilities of small and medium-sized enterprises in emerging markets.

The marketing capabilities of SMEs in EMs are crucial to enabling a competitive advantage to improve performance, and the intensity of competition explains the relationship between marketing capabilities and SMEs’ performance in EMs. Park et al. (2019) found that marketing capabilities support a competitive advantage and have a positive effect on export SMEs’ performance. Furthermore, Park et al. (2019) researched the effect of technology and market dynamism on the business performance of SMEs by supporting services, arguing that SMEs’ support services have a direct effect on their performance.

Giantari et al. (2022) studied the role of digital marketing in mediating the effect of the COVID-19 pandemic and the intensity of competition on business performance. They discovered that the effect of the COVID-19 pandemic and the intensity of competition on business performance was negative and significant. Thus, the adoption of digital marketing was unable to mediate the effect of the COVID-19 pandemic and the intensity of competition on SMEs’ performance. However, the adoption of digital marketing was incapable of mediating the effect of the COVID-19 pandemic and the intensity of competition performance. Adomako et al. (2017) researched the moderating influence of competitive intensity on the relationship between CEOs’ regulatory foci and SME internationalisation, and they found that competition is intense in the domestic market and the potency of a CEO’s promotion focus as a driver of internationalisation is amplified. Therefore, the following hypothesis is proposed in this study:

H6.

Competition intensity has a positive moderating effect (mediating role) of DMCs on SMEs’ business performance in EMs.

3. Research methodology

3.1 Questionnaire design and model constructs

Companies using digital marketing in Ghana constitute the universe of the research. In total, 178 Ghanian companies’ digital marketing activities constitute the research sample. The number of employees, business models and digital marketing activities used by the companies in the questionnaire form are given in Table 2, according to which SMEs use website content the most, at 76.4%, and mobile sales assistants the least, at 14%, in their digital marketing activities. There were 38 items in the questionnaire form, and Figure 2 shows the constructs and scales of the model.

3.2 Research model and analysis

SEM is a comprehensive tool that adopts a confirmatory approach to the analysis of a structural theory and allows the testing of hypotheses about the relationships between observed and latent variables. It is a statistical method used in many scientific disciplines to explain the interrelationships between a series of variables by combining factor analysis and multiple regression analysis. SEM can work simultaneously in the analysis of hypotheses for all variables of the research model (McLean et al., 2018, p. 329). The researchers are motivated to use SEM because it inspires enthusiastic praise as well as persistent rejection, more than other statistical tools. SEM allows researchers to conduct and combine a vast array of statistical procedures, including multiple regression and factor analysis.

LISREL was used in the SEM analysis, and CFA was used as the first step in understanding the model in LISREL. CFA is a statistical technique used to verify the factor structure of a set of observed variables. To apply factor analysis, the KMO test was used to determine whether the sample size is sufficient for factor analysis. As the KMO value gets closer to 1, the perfection level of the data set increases.

Therefore, factor analysis can be performed for the relevant data set, as the KMO value resulting from the analysis is 0.912, which is a good indicator of the sample size considered in the study. The CFA results are given in Table 3. Factor loads are defined as correlations between factors and variables. In the social sciences, factor loads are accepted to be between 0.40 and 0.70, whereas in this study, they varied between 0.50 and 0.93. Because the DMC 5 expression on the DMC scale was 0.14, it was excluded from the scale. In addition, in the social sciences, it is accepted that the total variance is between 40% and 60%. Hence, the explained variance in this study was considered sufficient for a study of 72,896. Moreover, the fact that a Cronbach’s alpha value of 70% or more is acceptable shows that all scales are acceptable in this study.

Later, some modifications were carried out in this study, applied between the expressions CRO2 and CRO1, TEO2 and TEO1, TEO6 and TEO4, TEO9 and TEO8, DMC2 and DMC1, DMC7 and DMC6, DMC8 and DMC7, DMC10 and DMC9, DMC11 and DMC8 and MED2 and MED1. After the modifications, CFA was repeated, and the fit measures were calculated. Fit test statistics and the model evaluation represent the most critical steps of SEM, as the fit indices determine how well the sample data fit the model. The results of the fit indices are given in Table 4, which shows that the c²/SD, RMSEA, GFI, AGFI, NFI, NNFI, CFI, RMR and SRMR indices were considered to evaluate the fit indices and the fit of the model with the data. The fit value ranges accepted in the literature are shown in Table 4. It has been determined that the data obtained in the study are in the acceptable range of values (c²/SD = 2.09, RMSEA = 0.079, GFI = 0.71, AGFI = 0.67, NFI = 0.93, NNFI = 0.96, CFI = 0.96, RMR = 0.10, SRMR = 0.083). Thus, the model is generally confirmed.

A t-value above 2.58 indicates a positive and significant relationship between variables and that the t-values are within an acceptable range. Considering these values, it was examined whether the relationship was significant and positive for all variables. As Table 5 is examined, technological orientation (β = 0.78, p <0.01) has the greatest impact on DMCs, explaining them by 59%. Subsequently, social CRM competence (β = 0.71, p < 0.01) has an impact on DMCs, explaining 50% of them. Finally, customer relationship orientation (β = 0.64, p < 0.01) has the lowest effect on DMCs, explaining 38% of them. According to these findings, H1, H2 and H3 are accepted. Moreover, according to the results of the SEM analysis, DMCs (β = 0.55, p < 0.01) affect SMEs’ business performance, explaining it by 30%. Thus, H4 is accepted. Conversely, it has been determined that dynamism has a positive moderating effect on the effect of DMCs on SMEs’ business performance, whereas competition intensity does not have a positive moderating effect. According to these findings, while H5 was accepted, H6 was rejected.

4. Results and discussion

4.1 Results of H1

Customer relationship orientation has a positive direct effect on DMCs (β = 0.64, p < 0.01), though it has the lowest effect, explaining 38% of DMCs. Therefore, H1 is confirmed. Our finding is not consistent with the findings of Mohammed, who found no statistically significant relationship between customer relationship orientation and SME performance and no significant impact on DMCs. Furthermore, Al Asheq et al. (2021) and Pan et al. (2021) found that customer relationship orientation has no effect on SME performance. Our study complements the findings of Rupeika-Apoga et al. (2022) that digital orientation also has a positive direct effect on DMCs.

4.2 Results of H2

Social CRM competence in SMEs is positively related to DMCs in EMs. Subsequently, our analysis confirms that social CRM competence has a positive direct effect on DMCs (β = 0.71, p < 0.01) and explains 50% of DMCs. Thus, H2 is confirmed. Our study supports the findings of Al Asheq et al. (2021), Bamfo and Kraa (2019) and Rupeika-Apoga et al. (2022). Social CRM competence in SMEs is positively related to DMCs, but simultaneously, argue that CRM competence is positively associated with SMEs and DMCs.

4.3 Results of H3

Technological orientation in SMEs is positively related to DMCs in EMs. Thus, H3 is confirmed (β = 0.78, p < 0.01). Technological orientation (β = 0.78, p < 0.01) has the greatest impact on DMCs and explains them by 59%. Our finding is consistent with those of Al Asheq et al. (2021), Bamfo and Kraa (2019) and Rupeika-Apoga et al. (2022), who argue that e-marketing orientation, technological orientation and learning capability have a statistically significant impact on SME performance. Furthermore, Pan et al. (2021) discovered that technological orientation and customer orientation play a critical role in driving firms’ digital capabilities. According to these findings, H1, H2 and H3 are accepted.

4.4 Results of H4

DMCs are positively related to SME performance in EMs. Thus, H4 is confirmed. According to the results, DMCs (β = 0.55, p < 0.01) affect SME performance by 30%, so H4 is accepted. This means there is a DMC effect on DMCs that is mediated by digital transformation. Our finding is consistent with those of Qureshi et al. (2017) and Feng et al. (2017), who studied the relationship between marketing capabilities and SME performance and found it to be positive. In addition, Mathews et al. (2016) and Qureshi et al. (2017) examined the relationship between marketing capabilities and market performance and found it to be negative.

4.5 Results of H5

Dynamism has a positive moderating effect (mediating role) on the impact of DMCs on SMEs’ performance in EMs. Thus, H5 is confirmed (β = 0.50, p < 0.01), signifying that there is a positive effect of dynamism on DMCs and that it is mediated by digital dynamism. It has been determined that dynamism has a positive moderating effect on the effect of DMCs on SMEs’ performance. Our finding is in line with those of Bamfo and Kraa (2019) and Wardaya et al. (2019), whose research discovered that dynamic capability has a positive direct influence on DMCs and SME performance. Our finding also conflicts with that of Mohammed, who found that marketing capabilities (planning and implementation) do not play a mediating role in the relationship between CRM technology and business performance.

4.6 Results of H6

Because competition intensity does not have a positive moderating effect, H6 was rejected. Competition intensity has no positive moderating effect (mediation role) on the impact of DMCs on SMEs’ business performance in EMs. However, we found a statistically insignificant mediating effect of competition intensity on DMCs (β = −0.16, not significant), which resulted in the rejection of H6. In addition, we cannot confirm that digital capability has a direct positive effect on SMEs’ performance. DMCs have no direct positive effect, a finding consistent with that of Adomako et al. (2017), who also discovered that intense domestic market competition weakens the negative influence of a CEO’s preventative focus on a firm’s degree of internationalisation. Giantari et al. (2022) discovered that the COVID-19 pandemic and intensity of competition have a negative effect on business performance.

5. Conclusion

5.1 Theoretical implications

Previous studies on DMCs and SMEs’ business performance are still insufficient. The results of this study focus on the relationship between DMCs and SMEs’ business performance in the market environment, which involves dynamism and competition intensity. This study gives knowledge exposure to emerging economies as it proposes new methods of evaluating DMCs and the business performance of SMEs in Ghana. By developing a research model, this study has contributed to the SNT literature by evaluating it from an EM perspective.

5.2 Practical implications

These findings could be useful for the Government of Ghana, the National Board for Small Scale Industry and the Association Ghana Industries to implement DMC adoption, CRM, technological orientation and competitive orientation practices in SMEs in Ghana as an EM to gain a competitive advantage. SME policymakers in EMs must take advantage of DMCs to provide quality products and services to their target markets, while SME managers in EMs must leverage DMCs and the potential of the market environment to improve performance.

SME stakeholders must also develop DMCs and effectively manage the business with a focus on customer relationship orientation, social CRM competence and technological orientation. Meanwhile, SME practitioners must manage feedback using the principle of efficiency with a consumer and technologically oriented approach in their workflows to improve their performance in EMs, and SME owner/managers should give importance to customer relation orientation and social CRM competence elements for the business, considering the difficulty of retaining loyal customers.

5.3 Limitations and future research directions

In addition to all these contributions and implications, this study has several limitations. The conceptual framework of the model proposed in this study can be further developed in many other contexts. Examining dynamism and competition intensity as mediating variables in the model limits the study. Besides these market environment elements, digital loyalty, flexibility and efficiency variables can be added. SMEs’ business performance can be further expanded by adding the variables of international marketing performance and export performance. Another limitation is that this study covers Ghanian SMEs only, so in the future, this research can be extended to other countries for comparison. Thus, the limitations given above can be overcome in future studies.

Figures

Figure 1.

Figure 2.

Model constructs

Table 1.

Studies on the digital marketing capability in emerging market

Author(s)	Sample	Dimensions	External variables
Amelda et al. (2021)	100 bank employees in Indonesia	Digital marketing capabilities, digital technology and digital leadership	Business performance
Utomo and Susanta (2020)	81 SMEs in Indonesia	Digital marketing capabilities, innovation capabilities	Marketing performance
Wang (2020)	167 International businesses in Taiwan	Digital marketing capabilities, entrepreneurial orientation	International business performance
Herhausen et al. (2020)	169 business managers	Digital marketing capabilities (channels, social media, digital relations and digital technology)
Liu et al. (2020)	132 businesses in Taiwan	Digital marketing capabilities	International market performance
	211 SMEs in South Africa	Digital marketing capabilities, communication technology	Marketing performance
	522 businesses in Belgium	Digital marketing capabilities, market orientation, and the technology orientation	Business performance, customer relations performance

Source: Table by authors

Table 2.

Number of employees, business models and digital marketing activities

	Frequency	%
Number of employees
Less than 10	57	32
10–49	42	23.6
50–250	20	11.2
Over 250	59	33.1
Business models
B2B	112	62.9
B2C	114	64
B2G	31	17.4
Other	3	1.8
Digital marketing capabilities
E-mail marketing	91	51.1
Creating and publishing blog content	64	36
Creating website content	136	76.4
Creating Facebook content	100	56.2
Creating mobile content	76	42.7
Creating YouTube content	74	41.6
Search engine optimization	91	51.1
Reviewing online analytics (google analytics etc.)	72	40.4
Creating twitter content	72	40.4
Creating content on other social media sites	92	51.7
E-commerce site management and updating	68	38.2
Webinars, podcasts, and live streams	56	31.5
Mobile sales assistants	25	14

Source: Table by authors

Table 3.

SEM analysis

	Observed variables (items)	Error variances	Path coefficient	t-values	Cronbach’s alpha	R2
Customer relations orientation (CRO)	CRO1	0.48	0.59	8.24	0.777	0.47
	CRO2	0.36	0.80	9.21		0.76
	CRO3	0.23	0.88	7.37		0.66
	CRO4	0.69	0.55	5.90		0.29
Social CRM competence (SCRM)	SCRM1	0.51	0.70	8.12	0.839	0.49
	SCRM2	0.32	0.82	9.85		0.67
	SCRM3	0.22	0.89	10.24		0.79
Technology orientation (TO)	TEO1	0.43	0.75	8.75	0.953	0.60
	TEO2	0.30	0.84	15.64		0.72
	TEO3	0.46	0.74	10.23		0.54
	TEO4	0.26	0.86	12.22		0.73
	TEO5	0.21	0.89	12.68		0.80
	TEO6	0.06	0.86	12.22		0.73
	TEO7	0.21	0.89	12.73		0.81
	TEO8	0.38	0.79	11.03		0.62
	TEO9	0.41	0.77	10.76		0.61
	TEO10	0.47	0.73	10.10		0.56
Digital marketing capability (DMC)	DMC1	0.20	0.84	8.29	0.921	0.73
	DMC2	0.27	0.85	18.05		0.76
	DMC3	0.35	0.81	13.32		0.65
	DMC4	0.43	0.75	13.32		0.56
	DMC5	0.98	0.14	1.85		0.019
	DMC6	0.44	0.75	11.80		0.55
	DMC7	0.28	0.84	14.23		0.69
	DMC8	0.33	0.79	12.77		0.61
	DMC9	0.30	0.83	14.00		0.72
	DMC10	0.23	0.88	15.35		0.79
	DMC11	0.27	0.86	14.60		0.72
Market environment dynamism (MED)	MED1	0.58	0.65	8.60	0.738	0.50
	MED2	0.85	0.39	4.77		0.24
	MED3	0.64	0.60	7.85		0.37
	MED4	0.42	0.76	10.45		0.52
Market environment competition intensity (MEC)	MEC1	0.45	0.74	9.53	0.710	0.57
	MEC2	0.75	0.50	6.23		0.25
	MEC3	0.48	0.,72	9.27		0.51
Business performance (BP)	BP1	0.38	0.79	12.21	0.896	0.62
	BP2	0.21	0.89	4.71		0.79
	BP3	0.13	0.93	15.83		0.87
Control variables	CV1	0.51	0.70	8.12		0.49
	CV2	0.32	0.82	9.85	0.849	0.67

Notes:

Kaiser–Meyer–Olkin (KMO) = 0.912/Bartlett test of sphericity: Chi-square value: 5,924.490 p = 0.000 Explained variance: 72.896%

Source: Table by authors

Table 4.

The goodness of fit indexes and structural model of the research model

Constructs	Acceptability criteria	Model
χ2/SD	(χ2/SD ≤ 3)	1,354.99 / 646 = 2.09
RMSEA (root mean square error of approximation	0.05≤ RMSEA ≤0.08	0.079
GFI (goodness of fit index)	GFI ≥ 0.90	0.71
AGFI (adjusted goodness of fit index)	AGFI ≥ 0.80	0.67
NFI (normed fit index)	NFI≥ 0.97	0.93
NNFI (Non-normed fit index)	NNFI≥ 0.97	0.96
CFI (comparative fit index)	CFI≥ 0.97	0.96
RMR (root mean square residual)	RMR ≤0.05	0.10
SRMR (standardized RMR)	0.05 < SRMR ≤0.10	0.083

Source: Table by authors

Table 5.

Results of the research model

Hypothesis	Causal path	Standardized path coefficient	R²	t-values
H1	CRO → DMC	0.64	0.38	6.13
H2	SCRM → DMC	0.71	0.50	7.83
H3	TO → DMC	0.78	0.59	9.49
H4	DMC → BP	0.55	0.30	3.71
H5	DMC → MED → BP	0.50	0.40	3.30
H6	DMC → MEC → BP	0.16	0.008	1.18

Source: Table by authors

Table 6.

Descriptive statistics for computed variables

No. of items	Computed variables	Observations	Mean	SD	Min	Max
1	Customer relations orientation	178	4.68	0.489	2	5
2	Social CRM competence	178	4.54	0.489	3	5
3	Technology orientation	178	4.31	0.668	2	5
4	Digital marketing capability	178	4.43	0.587	3	5
5	Business performance	178	4.47	0.478	3	5
6	Market environment	178	4.59	0.463	3	5
	Overall SME performance	178	4.15	0.514	2.61	5

Source: Table by authors

Table 7.

Reliability and validity

Variables	Loading	Square root	AVE	Reliability	CR
Customer relations orientation	0.85	0.72	0.625	0.81	0.851
Social CRM competence	0.82	0.68	0.502	0.81	0.931
Technology orientation	0.72	0.61	0.664	0.81	0.819
Digital marketing capability	0.77	0.59	0.595	0.82	0.854
Business performance	0.75	0.56	0.791	0.86	0.715
Market environment	0.74	0.55	0.641	0.82	0.756

Notes:

Moreover, establishing convergent and discriminant validity to define the construct validity is also necessary. Table (7) by authors shows reliability and validity check results of each sub-dimension and construct. The table below shows that all measures are reliable, as their respective CR and Cronbach’s alpha are above 0.7. It also indicates that convergent validity is confirmed for all constructs in the outer model, given that all AVEs are greater than 0.5 (Fornell and Larcker, 1981);

CR = composite reliability; AVE = average variance extracted. All values exceeded the recommended threshold. Hence, this study achieved the unidimensional for the construct

Source: Table by authors

Table 8.

Correlation analysis

	Customer relations orientation	Social CRM competence	Technology orientation	Digital marketing capability	Business performance	Market environment
Customer relations orientation
Pearson correlation	1.0000
Significance
Social CRM competence
Pearson correlation	0.4089*	1.0000
Significance	0.0000
Technology orientation
Pearson correlation	0.6397*	0.5304*	1.0000
Significance	0.0000	0.0000
Digital marketing capability
Pearson correlation	0.7891*	0.6246*	0.5204*	1.0000
Significance	0.0000	0.0000	0.0000
Business performance
Pearson correlation	0.6366*	0.5329*	0.7528*	0.6146*	1.0000
Significance	0.0000	0.0000	0.0000	0.0000
Market environment
Pearson correlation	0.5280*	0.6907*	0.5570*	0.5255*	0.5275*	1.0000
Significance	0.0000	0.0000	0.0000	0.0000	0.0000

Note:

*All correlations are significant at the 0.05 level

Source: Table by authors