Abstract
Purpose: As traditional advertising gives way to customer-centric strategies such as content marketing (CM), this study aims to explore its impact on customer loyalty (CL) in the digital banking sector, focusing on online engagement and switching costs (SCs), while addressing the research gap in emerging markets.
Design/methodology/approach: A quantitative, cross-sectional research design was employed, with data collected from 401 participants who interacted with digital banking content. The data were analysed using partial least squares structural equation modelling (PLS-SEM).
Findings/results: The findings of this study reveal that CM significantly boosts CL by enhancing online engagement. In addition, SCs were found to partially moderate the relationship between CM and engagement. However, SCs did not significantly influence the direct relationship between engagement and loyalty, suggesting that engagement and perceived value may be more impactful than switching barriers.
Practical implications: These results provide actionable insights for banks looking to strengthen CL through tailored content and engagement strategies. They emphasise the importance of focusing on customer engagement and perceived value to foster loyalty in the digital banking context.
Originality/value: While previous research has focused on CM in various sectors, limited studies have specifically explored its impact on CL within the digital banking sector, particularly in emerging markets. This study fills this gap by examining the role of online engagement and SCs in shaping CL, offering unique insights for digital banking strategies in the evolving landscape of customer-centric marketing.
Keywords: content marketing; customer loyalty; online customer engagement; switching costs; digital banking; Sierra Leone.
Introduction
In today’s digital age, traditional advertising strategies are increasingly being replaced by customer-centric approaches such as content marketing (CM). This shift is driven by the transformative power of digital technology, which has fundamentally changed how companies engage with their audiences. Modern consumers seek authenticity, relevance and meaningful interactions that resonate with their evolving needs. Content marketing has emerged as a cornerstone of digital marketing, focusing on the creation and distribution of valuable content to attract and retain customers. Unlike traditional advertising, which prioritises product features, CM builds trust and nurtures lasting relationships by addressing customer needs (Lou & Xie, 2021; Wang et al., 2019).
Customer loyalty (CL) is a critical factor for sustained business success, as loyal customers provide stable revenue streams and act as brand advocates, enhancing a company’s reputation through positive word-of-mouth (Kim et al., 2024; Rather & Hollebeek, 2021). However, in the digital era, promoting loyalty has become more challenging because of lowered switching barriers, which make it easier for customers to explore alternative options. In this context, CM through engagements serves as a key differentiator, enabling banks to develop meaningful connections with their customers (Chaffey & Ellis-Chadwick, 2019).
Online customer engagement (OCE) has emerged as a crucial factor influencing CM and CL. Engagement encompasses customers’ cognitive, emotional and behavioural investments in their interactions with a brand, enhancing the relationship, cultivating trust and establishing satisfaction, which are fundamental to consumer loyalty (Ajina, 2019; Lou & Xie, 2021). Online customer engagement acts as the bridge connecting CM to loyalty, aligning with the principles of Value Co-Creation Theory and Social Recognition Theory. Through the lens of Value Co-Creation Theory, customers actively engage with a bank’s content by sharing, commenting or providing feedback, co-creating value that enriches their experience and fosters deeper emotional loyalty (Nguyen, 2024; Wang & Yang, 2024). Simultaneously, Social Recognition Theory highlights how OCE creates avenues for acknowledgement, such as personalised responses or social media interactions, validating customer contributions and strengthening emotional bonds (Rather & Hollebeek, 2021).
Switching costs (SCs) encompass the perceived financial, procedural and emotional obstacles to altering service providers, adding another critical dimension to this dynamic (Ganaie & Bhat, 2021; Willys, 2018). These costs can exacerbate the impact of OCE by encouraging customers to enhance their participation rather than pursue alternatives. Therefore, examining SCs as a moderator offers a more profound understanding of loyalty in intensely competitive sectors such as digital banking.
Despite the growing body of literature on CM and CL, significant gaps remain, particularly in the context of digital banking in emerging markets. While previous studies have explored the impact of CM on CL in various sectors, limited research has specifically focused on the digital banking sector, especially in emerging markets like Sierra Leone. This sector is crucial to the country’s economic growth and development (Kebe et al., 2024). The digital banking sector in Sierra Leone faces unique challenges in adopting digital transformation, such as limited internet penetration, infrastructure constraints and fierce competition from fintech firms (Buhler et al., 2024). These challenges underscore the critical importance of CL for sustained business success.
In this context, leveraging CM emerges as a strategic imperative for banks. By creating and distributing informative, educational and engaging content, banks can build meaningful connections with their customers, fostering deeper, long-term relationships (Bui et al., 2023; Du Plessis, 2022). This approach not only enhances customer engagement but also differentiates banks from their competitors, thereby strengthening CL. However, the specific pathways through which CM impacts CL, particularly in the context of OCE and SCs, have not been adequately explored in emerging markets. This gap in the literature limits the development of targeted and effective marketing strategies for banks in these regions.
Moreover, the role of OCE as a mediator between CM and CL has received limited attention. Understanding this mediating role is essential for banks to design content strategies that effectively enhance CL (Ajina, 2019; Rizkia et al., 2024). Similarly, the moderating role of SCs in the relationship between CM and CL remains underexplored. Given the increasing ease of switching in the digital era, understanding how SCs influence CL is crucial for developing effective retention strategies (Ganaie & Bhat, 2021; Willys, 2018).
Thus, this study aims to extend existing research on CL, CM, SCs and OCE in the Sierra Leonean banking industry. The objectives are (1) to examine the impact of CM and OCE on CL; (2) to explore OCE as a mediator between CM and CL; and (3) to assess the moderating effect of SC in these relationships. The proposed model suggests that effective CM and customer engagement can enhance trust, satisfaction and loyalty, helping banks retain customers and drive long-term success.
This study makes significant theoretical and practical contributions to the field of digital banking and CL. By integrating Value Co-Creation Theory and Social Recognition Theory, we provide a comprehensive framework for understanding the dynamics of CL in a digital context. Our findings offer actionable insights for banks looking to enhance CL through CM and engagement strategies, particularly in emerging markets. This research fills a gap in the literature by focusing on the digital banking sector in Sierra Leone, providing valuable insights for banks operating in similar contexts.
Literature review and hypothesis
Theoretical background
To understand the role of CM on CL within a digital context, it is essential to examine the following foundational theories, namely, Value Co-Creation Theory and Social Recognition Theory. These thoughts offer a conceptual framework for understanding how CM cultivates stronger ties with consumers.
Value Co-Creation Theory
The Value Co-Creation Theory is grounded in the Service-Dominant Logic (SDL) framework established by Vargo and Lusch (2004), which states that value is generated through collaborative interactions between firms and customers, rather than being exclusively produced by firms (Pathak et al., 2022). This signifies a shift from the old-fashioned goods-dominant logic, which viewed value as embedded in products. However, SDL emphasises that service is the core of exchange, with value realised through the service experience rather than product transactions, and this shift redirects business focus from product features to fostering meaningful relationships and interactions. In digital banking, value co-creation is crucial because of the proliferation of digital platforms that enable two-way communication and interaction while CM plays a central role in this course by offering customers opportunities to engage, contribute and personalise their interactions, turning them into active participants in creating value.
Social Recognition Theory
Social Recognition Theory emphasises the need for acknowledgement and validation in influencing customer behaviour and cultivating loyalty. Grounded in psychological and social theories, it posits that acknowledgement satisfies fundamental demands for identity, esteem and belonging (Honneth, 1996). This theory posits that public and personal recognition of customer contributions, such as showcasing user-generated material or addressing feedback, can strengthen emotional loyalty and social identity (Rather & Hollebeek, 2021). However, recognition-driven strategies, including personalised responses, public shoutouts and reward-based campaigns, motivate continued engagement and reinforce customers’ emotional bonds with the brand. By transforming interactions into relational value, this theory offers a powerful outline for understanding how CM can cultivate loyalty in digital environments (Hossain & Kibria, 2024; Vivek et al., 2012).
Empirical framework
The empirical establishment, which is based on current research that looks at the connection between OCE, SCs and CL in the banking sector, sheds light on how CM affects it.
Content marketing and customer loyalty
The goal of CM is to generate leads and sales by creating and disseminating high-quality, relevant content to a targeted audience, and studies demonstrate that effective CM strategies in banks can create value for customers, thereby building trust and commitment. Studies by Chen et al. (2023) and Rather and Hollebeek (2021) highlight that CM, particularly when personalised and relevant, fosters a sense of connection between customers and the bank, ultimately promoting loyalty through emotional and rational bonds. However, this aligns with findings from studies by Lou and Xie (2021), which show that high-quality CM strengthens the customer–brand relationship by providing useful information, enhancing perceived value and cultivating a positive brand image, essential factors for CL. This creates meaningful interactions that enhance engagement and retention, emphasising the need for tailored content to position the bank as a trusted partner, not just a service provider. Consequently, we postulate the following:
H1: CM positively impacts CL.
Content marketing and online customer engagement
By producing worthwhile content that appeals to target audiences, CM plays a critical role in improving OCE. Research has shown that CM – when designed to be interactive, informative and personalised – boosts engagement levels by enabling meaningful connections between banks and their customers. For instance, Lou and Xie (2021) and Rather and Hollebeek (2021) revealed that CM drives OCE, fostering loyalty and trust. They noticed that customers who interact with bank content on social media or apps show higher loyalty. Furthermore, Gensler et al. (2013) argued that social media content allows banks to engage customers directly, respond to their queries and foster a sense of community, and a vibrant social presence enhances the effectiveness of influencer campaigns by making consumers feel as though they are engaging in a more intimate, authentic environment, thus boosting purchase intentions. Thus, built on the aforementioned, the following hypothesis is proposed:
H2: CM significantly enhances OCE.
Online customer engagement and customer loyalty
As banks increasingly digitise their services, engaging customers online has become essential to fostering loyalty, trust and a positive brand image. Studies have underscored the role of personalised and interactive digital experiences in strengthening the emotional and behavioural connections between customers and banks. Online customer engagement is a powerful predictor of loyalty. According to studies by Ng et al. (2020) and Windasari et al. (2022), customers who are actively involved with a bank’s digital material are more likely to stay loyal. Furthermore, consumers need to perceive value in a brand to engage actively with it, and Kilumile and Zuo (2024) added that consumer brand co-creation behaviour motivates consumers to become active brand advocates. This involvement, often stimulated by influencers, transforms passive followers into dedicated advocates, thereby strengthening brand loyalty and enhancing purchase intentions. In addition, Perez Benegas and Zanfardini (2023) argued that online engagement boosts loyalty by increasing perceived value, while Gensler et al. (2013) and Hossain and Kibria (2024) emphasised social media as a key driver for customer engagement, which can positively impact CL. In light of the foregoing, the following hypothesis is put forth:
H3: OCE significantly impacts CL.
The mediating effect of online customer engagement
From the literature, CM provides informative and relevant materials that attract customers, while OCE deepens this connection, ultimately fostering loyalty. However, research supports this pathway, demonstrating that CM alone is often insufficient to secure loyalty; rather, it is the degree of involvement it fosters that solidifies long-term commitment.
Studies by Ajina (2019); Bui et al. (2023); Chen and Xu (2022) and Du Plessis (2022) claim that CM significantly enhances CL when it is accompanied by high engagement levels. These studies support that content, such as financial education or personalised product recommendations, initially draws customers into businesses, and it is through interactive digital engagement – such as feedback channels, Q&A sessions and responsive social media interactions – that this content translates into loyalty (Chen et al., 2022).
Also, Ting et al. (2021) examined the indirect influence of social interactivity between customer engagement and brand loyalty. Consumer engagement behaviour and brand loyalty were positively affected by social interaction, according to the study, indicating that customers who interact with content are more inclined to develop positive emotional connections with the bank, thereby enhancing their loyalty. Similarly, research by Perez Benegas and Zanfardini (2023) reveals a favourable connection between the cognitive dimension of customer engagement (attention) and the emotional dimension (enthusiasm), indicating that capturing customer attention is crucial for fostering emotional engagement. However, these empirical investigations collectively indicate that OCE can mediate the link between CM and CL, leading to the formulation of the hypothesis below:
H4: OCE mediates the interaction between CM and CL.
The moderating impact of switching costs
The moderating role of SCs on the connection among CM, OCE and CL has garnered considerable interest in marketing research and studies show that SCs significantly influence both customer engagement and loyalty, strengthening retention and interaction with branded content. Research on SCs and CM highlights that these costs shape customer interactions with brands. Ha et al. (2023) reported that high SCs enhance CL, which in turn increase engagement with branded content. Similarly, Ganaie and Bhat (2021) argued that SCs serve as retention barriers, motivating customers to engage more with CM to justify their continued association with a brand. Also, Jones et al. (2007) suggested that SCs create a sense of obligation among customers, deepening content engagement, while Willys (2018) confirmed that financial and relational SCs reinforce both loyalty and engagement by intensifying customers’ brand commitment. Nevertheless, SCs not only mediate but also amplify CM’s impact on engagement, encouraging customers to maintain involvement with brand activities:
H5: SCs moderate the relationship between CM and OCE.
In terms of engagement and loyalty, SCs also moderate this relationship by enhancing loyalty through increased engagement. However, Chang and Chen (2008) found that higher SCs boost e-loyalty by sustaining engagement, and Lee et al. (2001) reported that customers perceiving high SC are more inclined to remain engaged, thus reinforcing loyalty. Furthermore, Ganaie and Bhat (2021) emphasised that SCs act as exit barrier, driving deeper brand commitment, and Willys (2018) supported that high SCs increase both engagement and loyalty outcomes. In addition, Jones et al. (2007) found that managing SCs effectively can optimise engagement strategies, leading to higher loyalty rates. In addition, Blut et al. (2014) posited that satisfaction, service value and loyalty can be turned into long-term commitments when SCs are substantial. Thus, building on these insights, the subsequent hypothesis is suggested:
H6: SCs moderate the relationship between OCE and CL.
Thus, this study’s conceptual framework (Figure 1) links CM, OCE, SCs and CL. It posits that strong CM drives high engagement, which in turn fosters loyalty, with OCE serving as the key mediator and SC serving as the moderating variable.
Methodology
Research design
The research used a quantitative, cross-sectional methodology to examine the relationship between CM and sustainable consumer loyalty, focusing specifically on the identification of possible moderating and mediating variables. Data were collected through a structured survey, and analysis was conducted using partial least squares structural equation modelling (PLS-SEM). Partial least squares structural equation modelling is effective in addressing complex, multivariate relationships and is well-suited for analysing moderated-mediation models, as supported by previous studies (Hair et al., 2021).
The study focuses on consumers within the Sierra Leonean banking sector who actively engage with digital content disseminated by commercial banks across various platforms. To ensure a comprehensive and representative sample, a structured online questionnaire was meticulously developed and distributed. This approach allowed us to capture detailed insights from respondents who regularly interact with digital banking content.
To achieve a balanced and representative sample, a stratified sampling method was initially employed. This involved dividing the population into distinct strata based on key demographic and behavioural characteristics, such as age, gender and frequency of digital content engagement. Following this, random sampling techniques were applied within each stratum to select participants. This method ensures that each subgroup within the population has an equal opportunity to be represented in the study, thereby enhancing the generalisability of the findings.
The study aimed to target a sample size of 500 participants. However, because of the complexities and challenges inherent in data collection, particularly in the context of digital engagement and response rates, the final sample size was 401 respondents. Despite this reduction, the achieved sample size remains robust and appropriate for the PLS-SEM analysis employed in this study. According to Hair et al. (2021), a sample size of at least 300 is recommended for reliable path analysis, especially when examining complex models involving mediated and moderated relationships. Therefore, the sample size of 401 respondents not only meets but exceeds this recommended threshold, ensuring the reliability and validity of the study’s findings.
Moreover, the study adhered to rigorous ethical standards. Before participating, individuals were thoroughly informed of the study’s goals, objectives and procedures. Informed consent was obtained from all participants, ensuring that they were fully aware of the nature of the study and their voluntary participation. This ethical approach not only protects the rights and interests of the participants but also enhances the credibility and integrity of the research.
Measures
Content marketing
The content marketing scale was designed to assess respondents’ perceptions of the quality, relevance and value of the content provided by digital banking services. The scale consists of five items measured on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree), adapted from Kim and Ko (2012). The items are mentioned in Table 2.
Online customer engagement
The OCE scale was designed to capture the cognitive, emotional and behavioural aspects of customer engagement. The scale consists of six items measured on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree), adapted from Vivek et al. (2012). The items are mentioned in Table 2.
Switching costs
The SC scale was designed to assess the perceived financial, procedural and emotional barriers to switching to another digital banking service. The scale consists of seven items measured on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree), adapted from Burnham et al. (2003). The items are mentioned in Table 2.
Customer loyalty
The CL scale was designed to measure respondents’ commitment and intention to continue using their current digital banking service. The scale consists of four items measured on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree), adapted from Zeithaml et al. (1996). The items are mentioned in Table 2.
Demographics
In this study, 52% were female respondents (210) and 48% were male respondents (191). The predominant age demographic was between 25 years and 34 years (49%), followed by 35–44 years (25%). Most respondents held a master’s degree (48%), with 23% holding a bachelor’s degree. Daily engagement with CM was reported by 67%, followed by weekly engagement (23%). The details are contained in Table 1.
Ethical considerations
Ethical clearance to conduct this study was obtained from the Beijing Jiaotong University’s Department of Business Administration Ethics Committee (No. 20240125).
Results
This research used PLS-SEM, a reliable analytical technique widely regarded in management and social science research for its capability to handle complex models, accommodate smaller sample sizes and deliver robust estimates of path coefficients and latent variable relationships. Comprehensive tests were carried out to guarantee the measurement model’s integrity. These tests are essential for confirming the precision and dependability of the constructs and provide a strong foundation for further structural model analysis (Fornell & Larcker, 1981).
Measurement model assessment
The validity and reliability of the measurement model were assessed prior to hypothesis testing. Indicator reliability was confirmed by item loadings, all exceeding the 0.70 threshold (Table 2), ensuring item reliability (Cardella et al., 2021). The SC construct initially had seven items, but three were removed because of low loadings, leaving the remaining items above the reliability threshold. Composite reliability (CR) exceeded 0.70 for all constructs (Table 2), confirming internal consistency. Convergent validity was established with average variance extracted (AVE) values surpassing the required threshold (Aydin et al., 2024). Discriminant validity was assessed using both the Fornell–Larcker criterion and the HTMT ratio, with all HTMT values below 0.90, confirming distinct constructs (Henseler et al., 2015). The Fornell–Larcker criterion (Table 3) further demonstrated that the square root of each construct’s AVE exceeded its correlations with other constructs (Fornell & Larcker, 1981). These results validate the measurement model for structural model analysis.
| TABLE 2: Validity and reliability of constructs. |
Hypothesis testing results
A bootstrapping technique with 5000 re-samples was performed to determine the significance of the path coefficients. This rigorous approach ensures reliable estimates and enhances the robustness of the findings by providing a comprehensive assessment of the statistical significance of each hypothesised relationship (Sarstedt et al., 2022). However, the model’s explanatory power (Table 2) is reflected in the R-square values, with CL explaining 71.5% of the variance (R2 = 0.715) and a high predictive relevance (Q2 = 0.442). For OCE, the model explains 32.1% of the variance (R2 = 0.321), with a moderate predictive relevance (Q2 = 0.309).
The findings presented in Table 4 demonstrate that CM positively influences CL as shown in the result (β = 0.278, t = 8.687 and p < 0.001), supporting H1. Similarly, CM has a strong positive effect on OCE, as evidenced in the result (β = 0.544, t = 13.405 and p < 0.001), thereby validating H2. In addition, OCE strongly impacts CL as revealed in the result (β = 0.604, t = 22.104 and p < 0.001), supporting H3. The mediation results indicate a significant effect of OCE on the link between CM and CL and the results (β = 0.329, t = 12.174 and p < 0.001), thereby supporting H4. Furthermore, the moderation results provide insights into the effects of SC on the relationships involving CM, OCE and CL. The outcome of H5 (β = 0.070, t = 2.082 and p = 0.037) indicates the statistical significance, and this confirms that SC positively moderates the relationship between CM and OCE, suggesting that the presence of SCs strengthens the effect of CM on customer engagement, thereby supporting H5. Conversely, the outcome of H5 (β = 0.057, t = 1.809 and p = 0.070) suggests that the results are not statistically significant. Although the path coefficient indicates a positive moderation effect, the t-statistic is below the critical value of 1.96, leading to the rejection of H6. The findings indicate that SCs do not significantly moderate the relationship between OCE and CL.
Thus, the structural model analysis of constructs (Figure 2) reveals important insights into the moderating role of SCs in the relationship between CM, OCE and CL. The model suggests that CM significantly drives OCE and CL, with OCE acting as the key mediator in this process. The results further suggest that SCs strengthen the effect of CM on customer engagement but do not significantly moderate the relationship between OCE and CL, as the moderation effect is not statistically significant.
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FIGURE 2: Structural model analysis of constructs. |
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The empirical evidence from our study supports the significant impact of CM on CL through OCE. The high explanatory power of our model (R2 = 0.715 for CL and R2 = 0.321 for OCE) underscores the strength of our findings and the validity of our arguments. Our results demonstrate that CM significantly boosts CL by enhancing OCE, with OCE acting as a critical mediator in this process. The moderating effect of SCs on the CM–OCE relationship further highlights the complexity of these dynamics in the digital banking sector.
Discussion
This section interprets the study’s findings by probing into the effects of CM, OCE and SCs on CL within commercial banks in Sierra Leone. Each hypothesis is reviewed in relation to relevant literature.
Content marketing’s positive impact on customer loyalty
The findings reveal that CM positively impacts CL, which validates Hypothesis 1 (H1). These results are consistent with previous studies. Additionally, Ajina (2019) found that CM enhances customer engagement and trust, essential elements of CL in the health care industry. Similarly, Siti Julaeha (2024) underscored that well-crafted CM strategies boost brand loyalty by nurturing meaningful customer relationships. Research by Bui et al. (2023) and Lou and Xie (2021) validates this perspective, demonstrating a robust positive link between CM efforts and CL metrics across diverse sectors. They argued that effective CM is crucial to customer satisfaction and brand loyalty. Collectively, these studies highlight CM as a critical driver in building and maintaining CL.
Link between content marketing and customer engagement
The study reveals a strong positive effect of CM on OCE, consistent with recent research. A study by Savitha and Roopa (2023) shows that effective CM significantly boosts engagement across digital platforms, with a clear link between content quality and user interaction. Similarly, Du Plessis (2022) highlighted that well-executed content strategies drive higher engagement levels, reinforced by the study’s result. Furthermore, Rizkia et al. (2024) stated that engaging content enhances interaction and purchase intentions, and eventually loyalty. These findings collectively emphasise CM’s critical role in driving OCE within commercial banks.
Relationship between online customer engagement and customer loyalty
The study’s results indicate that OCE significantly enhances CL, corroborating previous research. In a recent study, Srivastava et al. (2023) found that OCE significantly enhances CL across digital platforms, showing that high engagement levels correlate with increased loyalty metrics. In addition, Ahmad et al. (2022) underscored OCE as a pivotal mediator in the correlation between online customer experience and loyalty, asserting that engaged customers are more inclined to sustain enduring brand relationships. A study by Monferrer et al. (2019) further reinforces that effective engagement strategies are essential for encouraging loyalty behaviours. They argued that higher engagement levels directly correlate with increased loyalty, suggesting that companies should prioritise building engaging, interactive and personalised experiences to cultivate a loyal customer base. Hence, these studies confirm our hypothesis on the significant role of OCE in enhancing CL.
The mediating role of online customer engagement
Hypothesis (H4) suggests that OCE significantly mediates the connection between CM and CL and is well supported by existing research. Siti Julaeha (2024) confirmed that OCE mediates this connection, showing that effective CM enhances engagement, which subsequently strengthens loyalty. However, high levels of engagement, driven by effective content CM, lead to increased CL. This underscores the importance of OCE as a vital link between CM and CL.
However, Ahmad et al. (2022) further reinforced this by demonstrating that OCE mediates between CM and loyalty behaviours, aligning with our findings that engaged customers show stronger loyalty intentions. Furthermore, OCE connects CM to CL, suggesting that higher engagement levels foster CL, and Tuti and Sulistia (2022) emphasised the importance of OCE in enhancing loyalty through content, highlighting that engaged customers tend to remain more loyal. Consequently, these findings validate OCE’s essential mediating function, demonstrating that CM, when it fosters interaction, significantly aids in cultivating loyal customers.
The moderating role of switching costs
Hypothesis 5 shows that the relationship between CM and OCE is moderated by SCs, and the current literature supports this finding. A study by Mofokeng (2020) highlights that higher SCs can enhance the influence of marketing strategies on customer engagement, demonstrating that when SC is high, CM efforts yield stronger engagement outcomes. Li et al. (2024) also found that SC significantly affects how CM influences OCE, reinforcing the hypothesis on SC’s moderating role. Similarly, Ha et al. (2023) provided empirical evidence that higher SC strengthens the effectiveness of CM in fostering customer engagement, supporting the study’s findings. Moreover, Iqbal et al. (2023) also found that SC moderates the relationship between customer satisfaction and loyalty, which aligns with the study’s findings. Furthermore, Lee et al. (2001) confirmed that SC significantly influences engagement outcomes, supporting the moderating role of SC in marketing strategies. Thus, these studies affirm the significant role of SC in strengthening the impact of CM on OCE.
Conversely, hypothesis (H6) positing that SC would regulate the association between OCE and CL was not substantiated by the study’s data, resulting in the rejection of H6. This outcome suggests that SC does not considerably affect the OCE–CL relationship strength, contrasting with prior studies. For instance, Burnham et al. (2003) found that SC can drive customer retention by discouraging brand switching, while Lam et al. (2004) observed that high SCs enhance loyalty by making it costlier for customers to disengage, reinforcing OCE’s role in loyalty. However, Jones et al. (2007) showed that SC often strengthens loyalty by deepening customers’ commitment to frequently engaged brands. Nonetheless, Gremler (1996) argued that SC’s effect may vary across industries and demographics, aligning with this study’s results where SC did not significantly influence OCE–CL. Also, Woisetschläger et al. (2011) further observed that SC’s impact could lessen when loyalty is predominantly influenced by the calibre of engagement, and Daouk et al. (2021) suggested that higher SC can enhance retention, as customers may remain despite dissatisfaction because of perceived SC, highlighting SC’s variable influence on loyalty across different contexts. Thus, these sources underscore that while SC can moderate relationships in some cases, it does not universally enhance loyalty, supporting the lack of moderation effect observed in the study.
Contribution and argumentation
Our study makes significant theoretical and practical contributions to the understanding of CL in the digital banking sector. By integrating Value Co-Creation Theory and Social Recognition Theory, we provide a comprehensive framework for understanding the dynamics of CL in a digital context. Our findings offer actionable insights for banks looking to enhance customer loyalty through CM and engagement strategies, particularly in emerging markets.
Our empirical evidence supports the significant impact of CM on CL through OCE. The high explanatory power of our model (R2 = 0.715 for CL and R2 = 0.321 for OCE) underscores the strength of our findings and the validity of our arguments. Our results demonstrate that CM significantly boosts CL by enhancing OCE, with OCE acting as a critical mediator in this process. The moderating effect of SCs on the CM–OCE relationship further highlights the complexity of these dynamics in the digital banking sector.
Conclusion
This research underscores the pivotal significance of CM in building CL in the digital age. Integrating Value Co-Creation Theory and Social Recognition Theory demonstrates that customer engagement serves as a critical mediator between content marketing and loyalty. Content marketing fosters collaboration and recognition, deepens trust, strengthens emotional bonds and ultimately enhances loyalty. These findings emphasise the importance of interactive and personalised content that positions customers as co-creators and validates their contributions.
Theoretical implications
This research enhances the Value Co-Creation Theory and the Social Recognition Theory by broadening their applicability within the field of digital banking and consumer loyalty. The results align with previous research, demonstrating that CM and customer engagement play crucial roles in promoting CL, especially when mediated by OCE (Brodie et al., 2011; Rather & Hollebeek, 2021; Salonen et al., 2024). The study highlights the complex relationship between content marketing and loyalty, using OCE as a mediator, and supports earlier findings on the influence of customer engagement in strengthening customer–brand relationships (Chen & Xu, 2022; Vivek et al., 2012). Furthermore, the study enhances the understanding of SCs as a secondary influence on CL, particularly in the digital banking industry. While SCs do have some moderating effect, they are insufficient on their own to drive loyalty, reinforcing the idea that sustainable loyalty is primarily driven by perceived value and recognition rather than by barriers to exit alone (Blut et al., 2014; Chang & Chen, 2008). Therefore, by integrating these theories, the research bridges transactional and relational perspectives, demonstrating that CM strategies must combine value co-creation, recognition and engagement to build enduring loyalty within the digital banking sector.
Practical implications
This study provides useful information for policymakers and bank executives by highlighting how to use theories such as Social Recognition Theory and Value Co-Creation Theory to enhance loyalty in the digital age. Banks should prioritise creating high-quality, interactive and personalised content that enables customers to co-create value, as this encourages deeper engagement and emotional loyalty (Prahalad & Ramaswamy, 2004; Vargo & Lusch, 2004). Using platforms such as social media, mobile apps and the adoption of virtual assistants and chatbots will support collaboration and recognition. These solutions support real-time, tailored customer support, validate customer contributions and build trust through immediate acknowledgement, which supports the Social Recognition Theory (Hollebeek et al., 2019; Honneth, 1996). In addition, banks should develop community-driven strategies to enhance customer satisfaction and reduce churn (Kim et al., 2024; Monferrer et al., 2019). Through the establishment of virtual communities, such as user groups or forums, banks can promote belongingness and collaboration, and these platforms enable customers to share experiences, provide feedback and interact directly with the brand, which in turn strengthens emotional ties and customer retention. Moreover, banks can organise online events, webinars or co-creation challenges to encourage customers to participate in shaping products or services. This not only deepens engagement but also turns customers into brand advocates. Furthermore, rather than relying solely on traditional marketing, these strategies allow banks to shift towards relationship-focused, community-driven models. In competitive emerging markets, where customer choices are growing, these approaches are crucial for long-term retention. Also, offering exclusive content or engagement-based rewards can complement loyalty strategies without compromising customer trust. These recommendations provide a comprehensive guide for banks to align their strategies with changing customer expectations, leveraging co-creation, recognition and innovative technologies to drive sustained loyalty.
Limitations and future research directions
The focus of this study was on the banking sector in Sierra Leone, specifically looking at CL and the variables (CM, OCE and SC) that influence it. These factors may vary across different sectors (e.g. telecommunications and hospitality) and contexts, and therefore, researchers interested in this topic are advised to re-examine the proposed findings in other industries and countries. Further studies can explore the extent of Value Co-Creation Theory and Social Recognition Theory for other industries such as e-commerce, health care and education and draw generalisations. However, future research could examine additional mediating and moderating variables, like trust, digital literacy and customer satisfaction, which may provide deeper insights into the mechanisms driving CL in digital contexts. In addition, other researchers can investigate different cultures within sub-Saharan Africa, which might also add to the understanding of how culture impacts the extent to which CM strategies can enhance loyalty. Also, the potential of emerging technologies, such as artificial intelligence, machine learning and blockchain, to enhance or transform CM strategies can be examined. This study used a cross-sectional design, focusing on CL and factors such as CM, OCE and SC. Given the variability of these factors across sectors, future research should consider a longitudinal approach for broader applicability.
In summary, our study makes significant theoretical and practical contributions to the understanding of CL in the digital banking sector. By integrating Value Co-Creation Theory and Social Recognition Theory, we provide a comprehensive framework for understanding the dynamics of CL in a digital context. Our findings offer actionable insights for banks looking to enhance CL through CM and engagement strategies, particularly in emerging markets. This research fills a gap in the literature by focusing on the digital banking sector in Sierra Leone, providing valuable insights for banks operating in similar contexts. We believe that these contributions and arguments are robust and well supported by our research methodology and findings.
Acknowledgements
This article is based on research originally conducted as part of Agnes Caroline Dontina Mackay’s doctoral thesis, submitted to the School of Economics and Management, Beijing Jiaotong University in 2025. The thesis is currently unpublished and not publicly available. The thesis was supervised by Professor Zuo Li. The manuscript has been revised and adapted for journal publication. The authors confirm that the content has not been previously published or disseminated and complies with ethical standards for original publication.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
A.C.D.M. conceptualised the study approach, conducted the initial literature review, collected the data and wrote the first draft of the article as part of a PhD research project. L.Z. acted as a supervisor, contributed to and enhanced the article. I.A.K. helped to update the literature review section, reanalyse the data and enhance the results and discussion sections of the article.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author, A.C.D.M., 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 publisher. The authors are responsible for this study’s results, findings and content.
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