المجلة الرسمية لكلية التقنيات الإدارية جامعة النور

نوع المستند : Original Article

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Introduction

In light of the rapid transformations taking place in the digital world, technology, the internet, and social media have had a profound impact on reshaping the interactions between organizations and their audiences. Companies have shifted from traditional communication models to more modern strategies based on digital platforms, seeking to build long-term relationships with customers and enhance their competitive presence in the market. In this context, "digital content" has become a key component of digital marketing strategies, given the opportunities it provides to provide valuable information, generate ongoing engagement, and enhance customer loyalty.

Despite the widespread attention that social media marketing has received, there remains a knowledge gap regarding understanding the direct role of digital content in supporting sustainable competitiveness for organizations. Organizations' success in producing high-quality content relevant to their audiences' interests not only gives them an immediate advantage, but also contributes to building a strong, hard-to-imitate digital identity, supporting their sustainability and superiority in an environment characterized by increasing competition and changing consumer expectations.

The importance of this research lies in two main dimensions: the first is objective, representing the need for a deeper understanding of the importance of digital content as a strategic tool for achieving marketing excellence, and the second is applied, representing the provision of practical recommendations to organizations on how to improve their marketing performance through effective digital content. The research also seeks to shed light on a dimension often overlooked in contemporary studies: sustainability in achieving competitive advantage, making this work a qualitative addition to the relevant literature.

The research problem stems from the reality of the contemporary business environment, characterized by intense competition, which makes it necessary to explore new tools to enhance institutional excellence. Despite the growing reliance on digital content, the extent of its actual contribution to achieving a sustainable competitive advantage still requires careful study. Hence, the main question of this research arises: How do digital content strategies via social media contribute to achieving a sustainable competitive advantage for organizations? This question stems from a set of sub-questions, including: What characteristics should digital content possess to achieve marketing effectiveness? How does digital interaction affect customer loyalty and trust? And what is the relationship between content quality and brand image in the minds of the public?

2.Litriture Review And Hypothese Development

The marketing environment has undergone a major transformation in recent years due to digital advancements, with organizations increasingly relying on digital content as a pivotal tool for building relationships with audiences and achieving their promotional goals. Numerous studies have addressed this transformation, highlighting the profound impact of digital content on consumer behavior, marketing effectiveness, and an organization's competitive advantage (Karem et. al, 2022).

Kaplan & Haenlein (2010) indicated that engaging with audiences through digital content enhances customer engagement and contributes to expanding the follower base, which is a key indicator of effective marketing performance. In the same vein, Raewf et. al, (2021) explained that content marketing represents a long-term strategy focused on building trust and providing added value to the audience, rather than simply directly promoting products or services.

On the other hand, Tiago & Veríssimo (2014) demonstrated that the systematic use of digital tools contributes to achieving advanced organizational performance by enabling organizations to communicate effectively with customers and understand their needs. Chaffey & Ellis-Chadwick (2019) also demonstrated that interactive content is an effective tool for increasing audience engagement with a brand and stimulating a sense of belonging and emotional connection, which positively impacts loyalty and trust.

Ashley & Tuten's (2015) study supported this trend, explaining that the quality of social media content plays a key role in building brand image and improving customer perception. The researchers emphasized that visual elements, storytelling, and consistency in messaging collectively contribute to deepening the relationship between an organization and its target audience.

Lemon & Verhoef (2016) emphasized that the rich digital experiences created by organizations through interactive content are able to directly influence the customer journey, increasing the likelihood of converting from a follower to an actual consumer.

In a recent analytical study, Hollebeek & Macky (2019) found that value-based engagement—when consumers feel that content addresses their needs and provides real value—is one of the most important factors contributing to a sustainable competitive advantage, especially in a digital environment characterized by saturation and multiple options.

Based on this literature, the importance of digital content—in terms of quality, interactivity, and creativity—is clearly evident as key elements in enhancing marketing performance and enabling organizations to achieve sustainable superiority in a highly competitive market. Based on this, the following hypotheses can be formulated, which represent the foundations of the current research:

H1: There is a statistically significant positive relationship between digital content and enhancing customer relationship.

H2: Digital content has a direct, statistically significant positive effect on sustainable competitive advantage.

H3: Enhancing customer relationship positively influences the organization’s sustainable competitive advantage.

These hypotheses represent the analytical framework for the study and will be tested using field data collected from an active target audience on social media, in order to verify the validity of the relationship between digital content variables and the desired marketing outcomes.

Figure 1.Conceptual Model

3.Methodology

This research is based on the quantitative approach, where statistical data analysis tools were used to test the relationships between the studied variables as stated in the conceptual model.

Additionally, a descriptive-analytical research design was adopted to describe and analyze the impact of digital content via social media on enhancing customer relationships and its impact on achieving sustainable competitive advantage. The research sample consists of active customers through social media. A simple random sample was selected, and the sample size was between 107 customers.

However, a structured questionnaire designed using a five-point Likert scale was used to measure the research variables. Data were analyzed by SMART PLS 4 software.

4.Data Analysis and Results

4.1 Validity of Measurement Model

The validity of a measurement model depends on its ability to accurately represent the target construct or model. This part is crucial in research because it ensures the reliability and significance of the measurements used in the study. According to Kline (2013), a measurement model examines latent or composite variables. Additionally, Hair et al., (2019) propose two criteria for assessing the validity of a measurement model: convergent validity and discriminant validity.

4.1.1 Convergent Validity

To assess convergent validity, factor loadings, composite reliability (CR), Cronbach's alpha (CA), and average variance explained (AVE) were calculated according to the method described by Fornell and Larcker (1981). Convergent validity is considered acceptable when the following three conditions are met: (a) CR values are 0.7 or higher, (b) variable loadings are 0.7 or higher, and (c) AVE values are 0.5 or higher (Hair et al., 2019).

According to the results shown in table 1, the measurement model appears to meet the construct reliability criteria, including CR, CA, factor loadings, and AVE. The CR values range from 0.724 to 0.912, reflecting a good level of internal consistency and high reliability of the measurement model. High CR values indicate that the indicators accurately and effectively measure the core components.

Construct Cronbach's alpha Composite reliability (ρa​) Composite reliability (ρc​) Average variance extracted (AVE)
Digital Content 0.832 0.838 0.888 0.664
Enhancing Customer Relationship 0.903 0.912 0.939 0.838
Sustainable Competitive Advantage 0.709 0.724 0.836 0.630
Table 1.Table 1 (Convergent Validity)

4.1.2 Discriminant Validity

Discriminant validity is assessed using the "trait-to-trait correlation (HTMT) ratio," where HTMT is calculated by comparing the average correlations between items across different variables with the average correlations between items within the same variables. According to Henseler et al. (2015), HTMT values greater than 0.90 indicate a lack of discriminant validity. Based on the results in table 2, all HTMT values are less than 0.90, indicating no discriminant validity issue.

Digital Content Enhanced Customer Relationship Sustainable Competitive Advantage
Digital Content
Enhancing Customer Relationship 0.338
Sustainable Competitive Advantage 0.523 0.473
Table 2.Table 2 (Discriminant Validity)

4.2 Assessment of Structural Model

The second step involves running the structural model, which involves examining the significance of the paths and the R² and Q² values for their predictive significance. As shown in Figure 2, the R² value for the model is 0.246, indicating that the independent variables explain approximately 24.6% of the variance in the dependent variable. The strength of each structural path, represented by the R² value for the dependent variable, is used to assess the quality or fit of the model.

According to Falk and Miller (1992), an R² value of 0.1 or greater is considered an acceptable criterion for the strength of a structural path. As shown in Figure 2 and table 3, an R² value of 0.246 exceeds this threshold, confirming the model's predictive power.

The results presented in table 3 and Figure 2 provide an in-depth analysis of the hypothesis testing and overall model evaluation. The results indicate that digital content has a significant and positive impact on enhancing customer relationships (β = 0.295, P = 0.004 < 0.05). This means that the quality, interactivity, and innovation of digital content contribute to building a more effective and trusting relationship with customers across social media platforms.

As for H2, which is that digital content positively affects achieving sustainable competitive advantage, this hypothesis was strongly confirmed (β = 0.338, P = 0.000), reflecting that organizations that produce unique and valuable digital content are able to build a competitive position that is difficult to imitate in the market.

However, for H3, which is that enhancing customer relationships positively affects achieving sustainable competitive advantage, the relationship between enhancing customer relationships and sustainable competitive advantage was also statistically significant (β = 0.277, P = 0.003), indicating that maintaining customer trust and loyalty contributes to achieving a long-term competitive advantage for the organization.

This suggests an indirect (partial mediation) effect of “enhancing customer relationships” between digital content and competitive advantage.

Original sample (O) Sample mean (M) Standard deviation (STDEV) T statistics (|O/STDEV|) P values
Digital Content -> Enhancing Customer Relationship 0.295 0.306 0.102 2.887 0.004
Digital Content -> Sustainable Competitive Advantage 0.338 0.347 0.094 3.579 0.000
Enhancing Customer Relationship -> Sustainable Competitive Advantage 0.277 0.275 0.092 3.018 0.003
Table 3.Table 3 (Hypothesis Testing)

Figure 2.

5. Suggestions And Recommendations

In light of the research findings, the researcher makes a number of practical recommendations that can contribute to enhancing the effectiveness of social media marketing and achieving a sustainable competitive advantage through digital content, as follows:

1.Focus on the quality of digital content:

Organizations should focus on producing high-quality digital content that is clear, accurate, and reflects the needs and preferences of their target audience. This has a direct impact on strengthening customer relationships and achieving digital marketing goals.

2.Enhancing digital engagement with the public:

The study recommends increasing engagement with followers by responding to comments, organizing contests, and encouraging participation, as these play a significant role in building trust and loyalty among customers.

3.Innovation and credibility in content delivery:

Organizations must adopt innovative approaches to designing and presenting content in an engaging manner, while maintaining a high level of credibility and transparency, as this plays a significant role in supporting the brand's image and enhancing its competitive advantage.

4.Investing in interactive content:

It is recommended to use different types of interactive content, such as videos, animations, and short surveys, to enhance the user experience and encourage engagement with the brand.

5.Employing digital analytics to evaluate performance:

The study encourages the use of digital analytics tools to evaluate the effectiveness of content and measure its impact on key performance indicators, such as engagement rates, loyalty, and purchase intentions.

Conclusion

In light of the rapid transformations in the digital business environment, digital content has become a pivotal tool that organizations rely on to enhance their market presence and build long-term relationships with their audiences. This research sought to shed light on the role digital content plays in strengthening customer relationships and achieving a sustainable competitive advantage across social media platforms.

The study results showed that content quality, interactivity, and credibility are essential elements in building trust and loyalty with audiences, which positively impacts long-term competitive advantage. It also demonstrated that digital customer engagement serves as an effective link between an organization and its audience, enhancing customer retention and converting them into brand advocates.

Through statistical analysis, the validity of the three hypotheses underlying the research's conceptual model was confirmed, reinforcing the importance of investing in digital content as an indispensable strategic option in a competitive and ever-changing digital environment.

Accordingly, this research represents a qualitative addition to the scientific literature in the field of digital marketing, and provides a practical framework that organizations can benefit from to improve their marketing performance and achieve sustainable competitive advantage by adopting effective and innovative digital content strategies.

References

  1. Ashley, C., & Tuten, T. (2015). Creative strategies in social media marketing: An exploratory study of branded social content and consumer engagement. Psychology & Marketing, 32(1), 15–27. https://doi.org/10.1002/mar.20761.DOI
  2. Chaffey, D., & Ellis-Chadwick, F. (2019). Digital marketing. Pearson UK.
  3. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312.DOI
  4. Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
  5. Hollebeek, L. D., Islam, J. U., Macky, K., Taguchi, T., Costley, C., & Smith, D. (2019). Personality-based consumer engagement styles: Conceptualization, research propositions and implications. In Handbook of research on customer engagement (pp. 224–244). Edward Elgar Publishing. https://doi.org/10.4337/9781788114899.00017.DOI
  6. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203.DOI
  7. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.DOI
  8. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003.DOI
  9. Karem, M. A., Raewf, M. B., Thabit, T. H., & Shakir, R. M. (2022). The factors that influence knowledge sharing in educational institutions. Cihan University-Erbil Journal of Humanities and Social Sciences, 6(1), 69–74. https://doi.org/10.24086/cuejhss.v6n1y2022.pp69-74.DOI
  10. Kline, R. B. (2013). Principals and practice of structural equation modeling. In Journal of Chemical Information and Modeling (Vol. 53, Issue 9). https://doi.org/10.1017/CBO9781107415324.004.DOI
  11. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. https://doi.org/10.1509/jm.15.0420.DOI
  12. Raewf, M., Aissa, S. A. H., & Thabit, T. (2021). The impact of quality, cost, and lead time on competitive advantage: Case of SMEs operating in Iraq. Economic Studies Journal, 19(03). https://ssrn.com/abstract=3945123.
  13. Tiago, M. T. P. M. B., & Veríssimo, J. M. C. (2014). Digital marketing and social media: Why bother? Business Horizons, 57(6), 703–708. https://doi.org/10.1016/j.bushor.2014.07.002.DOI
المجلد 1، العدد 0
يوليو 2025
الصفحة 29-33