The Effect of Brand Image on Organizational Attractiveness: The Mediating Role of Social Media Marketing in the Banking Sector

The Effect of Brand Image on Organizational Attractiveness: The Mediating Role of Social Media Marketing in the Banking Sector | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Effect of Brand Image on Organizational Attractiveness: The Mediating Role of Social Media Marketing in the Banking Sector Hawraa Mushtaq Talib, Sarah Ali Saeed Alameri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9612378/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract The study will examine the connection between brand image and organizational attractiveness by examining the mediating role of social media marketing (SMM) in the Iraqi banking sector, The paper, based on the signaling theory, re-conceptualizes SMM as a capability-based signal amplification process that converts latent brand characteristics into visible signals, thus alleviating information asymmetry ,The study design was a quantitative, cross-sectional research, in which 357 employees personnel were surveyed and the data were examined with the help of partial least squares structural equation modeling (PLS-SEM). The results confirm that brand image and SMM have a significant positive impact on organizational attractiveness, and the mediation analysis shows that SMM partially mediates and strengthens this relationship. The model has a moderate explanatory power and high predictive relevance, and PLSpredict proves better out-of-sample predictive performance, Theoretically, this study makes three key contributions. First, it redefines social media marketing as an active, capability-based signaling infrastructure, as opposed to a passive communication channel. Second, it provides a mechanism-based explanation of how brand image is operationalized into organizational attractiveness in the form of observable and interactive engagement processes. Third, it extends the existing body of research on signaling and employer branding by demonstrating how signals are amplified in dynamic and interactive situations, Managerially, the results point to the fact that organizations should not be content with the traditional brand-building, but they need to strategically plan interactive social media potentials to make organizations more attractive in competitive labor markets. This brings out an important contradiction between predetermined brand perceptions and dynamic signal amplification mechanisms. JEL Classification: M31, G21, M12, M37 Brand Image Social Media Marketing Organizational Attractiveness Digital Engagement Signaling Theory Employer Branding Partial Least Squares Structural Equation Modeling Emerging Markets Figures Figure 1 1. Introduction Although banks have traditionally used stable reputations over decades to instill trust in stakeholders in high-risk settings, the real-time interactivity of social media allows building or destroying brand equity in a short period of time, disrupting the conventional dynamics of trust (Althuwaini, 2022; Bernini et al., 2021; Vives, 2019). This is especially acute in the emerging markets like the banking sector in Iraq, where the digital transformation is gaining momentum in the face of economic instability, regulatory limitations, and talent shortages, making the organizational attractiveness a key factor in recruitment, retention, and competitive positioning (Alameri et al., 2024; Husseini, 2025; Jasim et al., 2026; Mado et al., 2025), Current studies assume brand image as a direct precursor of organizational attractiveness (Shahid and Ayyaz, 2023) and discuss the results of social media marketing (SMM) in terms of customer loyalty and employer branding (Salhab et al., 2023; El-Menawy and Saleh, 2023; Marquez-Oyakawa et al., 2025). Nevertheless, this literature is still theoretically disjointed. Previous research is mostly on direct effects or downstream outcomes, without integrative frameworks that describe the mechanisms between these constructs. As a result, there is still a critical gap in the literature, with studies not considering the role of SMM in mediating the transfer of brand image to organizational attractiveness in digitally disrupted banking contexts, as well as in under-researched emerging economies where information asymmetries are more pronounced., More to the point, this restriction inhibits the development of theory by obscuring the operationalization of intangible brand assets into stakeholder-based outcomes via digitally mediated processes. This poses a theoretical conflict between the symbolic quality of brand image and the visible processes needed to shape stakeholder perceptions in digital spaces. The disjuncture is particularly acute in the banking sector that is rapidly digitalizing and becoming more dependent on online platforms to influence customer interactions and brand perceptions (Al-Rdaydeh et al., 2025), where the process of symbolic brand value being transformed into visible stakeholder reactions is under-theorizedm In order to fill this gap, this paper will look at the mediating effect of social media marketing in the correlation between brand image and organizational attractiveness in the Iraqi banking industry. Based on the signaling theory, SMM is theorized as a system of visible digital cues that communicate latent brand qualities like credibility, reliability, and organizational values- to external stakeholders. Such signals decrease uncertainty and alleviate information asymmetries by converting abstract brand perceptions into tangible, interactive, and publicly verifiable signals, which increase organizational appeal (Carpentier et al., 2019; Thang and Trang, 2024). This study theoretically redefines social media marketing as a capability-based mediator that connects intangible brand resources to organizational attractiveness outcomes (Hafez, 2022; Laradi et al., 2023). By so doing, it builds upon previous studies that have largely concentrated on direct relationships or downstream effects like purchase intention and brand awareness (Bibi et al., 2025; Tarabieh, 2022), by elucidating the mediating processes between brand image and organizational-level implications, Contextually, the study is relevant as it places these mechanisms in the context of the Iraqi banking industry, which is a little-researched emerging market with institutional volatility, pressures of digital transformation, and changing stakeholder expectations. This background is especially pertinent in the light of the recent developments in strategic intelligence, the use of fintech, sustainability plans, knowledge management, organizational agility, and AI-based practices in banking (Al-Ameri et al., 2023; Almado & Algburi, 2025; Alameri et al., 2024; Saleh & Alameri, 2022; Salman et al., 2019; Mado et al., 2025)m Although the role of social media marketing in influencing stakeholder engagement is increasingly becoming significant, there is a paucity of empirical research investigating its mediating effect between brand image and organizational attractiveness specifically in the banking sector in developing economies (Hafez, 2022; Marquez-Oyakawa et al., 2025; ONUORAH et al., 2022; Shahid and To this end, the paper will utilize a strict mediation model to deconstruct the mediating processes between these constructions to offer a subtle insight into how social media use can be converted into organizational benefits in unstable and information-scarce contexts, In this way, this research contributes to a signaling-based account of how digitally mediated interactions transform intangible brand assets into tangible organizational outcomes in uncertain conditions. 2. Conceptual and Theoretical Foundation Brand image refers to the perceptions and mental associations of consumers or stakeholders with a brand, including tangible and intangible attributes that help to differentiate and create value (Korchia, 1999; Laradi et al., 2023; Tahir et al., 2024). Strategically, it is a vital intangible resource that influences stakeholder assessments and organizational positioning. Social media marketing (SMM), in turn, refers to the strategic use of digital platforms to engage customers and partners through activities such as entertainment, interaction, and trendiness, with the aim of enhancing brand awareness and fostering long-term relationships (Althuwaini, 2022; Laradi et al., 2023; Lilembalemba & Phiri, 2024). Organizational attractiveness refers to the perceived gains of being part of an organization, such as economic, developmental, and symbolic values like prestige and innovation (Dassler et al., 2022; El-Menawy & Saleh, 2023; Santiago & Tiago, 2025; Shahid & Ayyaz, 2023), Signaling theory, first formulated by Spence, deals with information asymmetry, where one party has better information about its quality than the receiver. To lessen this asymmetry, organizations send observable signals that provide credible information regarding latent characteristics. Low-quality signalers tend to be more expensive to provide effective signals, whereas high-quality signalers are cheaper to provide effective signals, which is a guarantee of reliability (Confetto et al., 2023; Connelly et al., 2010, 2024; Taj, 2016). Signaling theory is used in marketing and recruitment settings to describe how organizations use digital activities to convey credibility, minimize uncertainty, and increase trust among stakeholders (Carpentier et al., 2019; Thắng and Trang, 2024; Türker and Ünguren, 2025). But in digitally mediated spaces, signals are not simply sent, but are algorithmically edited, enhanced, and socially approved, changing their visibility, credibility, and interpretive effect, It is based on this view that this paper develops a signaling-based architecture where brand image is theorized as a latent signal aggregation construct that represents underlying organizational quality and values, and social media marketing is a capability-based signaling infrastructure that converts, amplifies, and broadcasts these signals into visible and interactive digital signals. By using SMM, organizations are actively involved in the construction, prioritization, and interpretation of signals in digital ecosystems, making them more cognitively accessible, less ambiguous, and allowing stakeholders to make more coherent judgments, The attractiveness of an organization is thus determined as the outcome of the cognitive evaluation of the stakeholders of these digitally mediated cues, particularly in cases of uncertainty. This process is particularly relevant in emerging economies like Iraq, where economic instability and institutional insecurity increase the dependence on visible digital indicators (Carpentier et al., 2019; Confetto et al., 2023; Laradi et al., 2023; Suprawan et al., 2025; Thắng & Trang, 2024), Based on this, this paper redefines social media marketing as not just a communication medium, but as a key signaling infrastructure that regulates the process of brand image into organizational appeal, which offers a single theoretical basis to the proposed relationships. 2.1. Brand Image and Organizational Attractiveness A strong brand image is a key factor that increases the attractiveness of the organization because it influences the perceptions of the stakeholders regarding the prestige, reputation, and overall value of the organization as an employer (Dassler et al., 2022; Davies et al., 2024; El-Menawy and Saleh, 2023; Santiago and Tiago, 2025). Empirical data always confirms that positive brand image perceptions have a positive impact on the assessment of potential employees, thus increasing organizational attractiveness in both instrumental (e.g., economic and developmental benefits) and symbolic (e.g., prestige and innovation) aspects (Erdil and Tatar, 2019; Santiago and Tiago, 2025; Shahid and Ayyaz, 2023)m Grounded in signaling theory, brand image is a high-level, aggregated cue that communicates organizational quality, credibility, and distinctiveness, thus decreasing information asymmetry between organizations and job seekers (Connelly et al., 2010; Davies et al., 2024; Heilmann et al., 2022). In contrast to discrete communication signals, brand image is a cumulative evaluative construct that combines various organizational cues into a consistent perception, which allows stakeholders to make holistic judgments in the face of uncertainty. This enhances cognitive fluency and reduces evaluative ambiguity thereby facilitating easier and more positive and confident judgments of organizational attractiveness, The success of such a relationship, though, is determined by the clarity, consistency and credibility of the underlying signals that constitute brand image, which means that not all brand images are equally converted into attractiveness. In the framework of the Iraqi banking sector, where the economy is unstable, and the digital transformation is an ongoing process, it is a strategic requirement to create a strong and consistent brand image to make the organization more appealing and recruit high-quality talent (Nwanebo, 2025; Thắng & Trang, 2024), Brand image is thus redefined not as a perceptual result, but as a strategic signal aggregation process that influences the cognitive processing and assessment of organizational value by potential employees. H1: Brand image positively influences organizational attractiveness by enhancing the cognitive evaluation and perceived credibility of employer-related signals. 2.2. Brand Image and Social Media Marketing Social media marketing can greatly improve brand image by spreading visible cues that communicate organizational prestige, innovation, and trustworthiness to stakeholders, especially potential employees (Carpentier et al., 2019; Kissel and Büttgen, 2015; Laradi et al., 2023; Thang and Trang, 2024). Empirical data show that social media marketing practices such as interaction, entertainment, trendiness, and informativeness have a positive influence on brand image perceptions, thus creating stronger employer associations in competitive labor market (Althuwaini, 2022; El-Menawy & Saleh, 2023; Lilembalemba & Phiri, 2024; Salhab et al., 2023; Suprawan et al., 2025; Tarabieh, 2022), Based on the signaling theory, social media marketing serves as a channel that helps to reduce information asymmetry by converting latent brand attributes into plausible digital signals that can be easily deciphered by the stakeholders. Notably, unlike previous studies that tend to conceptualize brand image as a precursor to social media engagement, this study takes a complementary and inverted approach by positing that social media marketing is a co-creative and redefining process of brand image in digitally mediated contexts. This is indicative of the dynamic and interactive quality of digital platforms, in which brand meaning is negotiated, amplified, and validated through ongoing processes of engagement and not passively conveyed, In the recruitment setting, job seekers are more likely to use the social media presence of organizations to make inferences about the quality of the employer and organizational attributes (Carpentier et al., 2019; Confetto et al., 2023; Connelly et al., 2010, 2024). Furthermore, the abundance of information presented in social media platforms increases the corporate image perceptions and employer brand ratings (Confetto et al., 2023; Kissel and Bueggen, 2015; Thang and Trang, 2024). In addition to transmission, social media platforms are algorithmically filtering and amplifying brand-related signals, making them more visible and perceived as more credible. This operation increases the cognitive accessibility and decreases ambiguity, which allows more coherent and positive brand image development, Nevertheless, the effect of social media marketing on brand image depends on the perceived authenticity, consistency, and credibility of communicated signals, which means that not all digital interactions have the same positive impact on the creation of positive images. The Iraqi banking industry, with its economic instability, digitalization, and lack of talent, is a place where strategic use of social media marketing is necessary to improve brand image, distinguish banks, and indicate stability in uncertain situations (Al-Hachami & Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022; Thắng & Trang, 2024), It is on this basis that social media marketing is re-conceptualized as a capability-based signal construction process that does not merely communicate brand attributes but in fact, affects the cognitive construction and evaluation of brand image in the digital space. H2: Brand image positively influences Social media marketing by enhancing the visibility, credibility, and cognitive accessibility of brand-related signals in digital environments. 2.3. Social Media Marketing and Organizational Attractiveness The immediate advantages of social media marketing are the enhanced appeal of the organization due to the interactive digital signals that potential employees interpret as an indicator of employer quality, workplace culture, and career opportunities (Carpentier et al., 2017, 2019). Empirical studies indicate that the features of social media, including social presence and informativeness, have a positive impact on employer brand attractiveness and job application intentions among potential applicants (Suprawan et al., 2025; Pham and Duy, 2022; Shahid and Ayyaz, 2023). Moreover, the perception of both instrumental and symbolic employer brand attributes is reinforced by exposure to organizational social media profiles. (Carpentier et al., 2017; Kissel & Büttgen, 2015), Grounded in signaling theory, social media marketing helps to decrease information asymmetry in the recruitment setting by converting latent organizational characteristics into visible digital signals on platforms where job seekers are actively seeking employer-related signals (Babikova and Bucek, 2019; Carpentier et al., 2019; Connelly et al., 2010, 2024). This viewpoint disputes previous studies that have mostly considered organizational attractiveness as a passive consequence of employer branding, by highlighting its active creation via dynamically mediated digital cues and interactive engagement procedures. This is particularly applicable in digitally mediated recruitment environments, where social media pages provide information about organizational values, diversity, and engagement, resulting in positive attitudes and word-of-mouth intentions (Brouer et al., 2021; Confetto et al., 2023; Türker & Üngüren, 2025), Besides the flow of information, social media platforms filter, amplify, and prioritize organizational cues, which are more visible and credible. This enhances cognitive access and reduces evaluative uncertainty, enabling potential employees to make more positive and confident judgments, The effectiveness of these signals, however, depends on how authentic, interactive, and consistent they are perceived, which implies that not all social media activities produce the same impact on the attractiveness of organizations. The economic instability, digitalization, and talent scarcity of the Iraqi banking sector precondition the necessity of strategic use of social media marketing to demonstrate the stability, innovation, and employee value propositions, raising the organizational appeal and application intentions (Al-Hachami & Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022), Based on this, social media marketing is redefined as a capability-based signaling infrastructure that does not merely convey organizational attributes but also actively influences the perception, evaluation, and internalization of these attributes by potential employees. H3: Social media marketing positively influences organizational attractiveness by enhancing the visibility, credibility, and cognitive accessibility of employer-related signals in digital environments. 2.4. Mediating Role of Social Media Marketing The connection between brand image and organizational attractiveness is mediated by social media marketing, which directs brand-related cues through interactive digital platforms that enhance the perceptions of organizational prestige, credibility, and quality among the stakeholders (Carpentier et al., 2019; El-Menawy and Saleh, 2023; Salhab et al., 2023; Tarabieh, Empirical data indicate that SMM enhances the connection between positive brand perceptions and employer ratings because organizations that actively use social media indicate greater attractiveness and application intentions among potential employees (Carpentier et al., 2017; Kissel & Büttgen, 2015; Shahid & Ayyaz, 2023; Suprawan et al., 2025), Grounded in signaling theory, social media marketing is a transmission system that transforms the fixed qualities of brand image into dynamic and visible digital messages, such as interactive content, user interaction, and informational richness, which stakeholders interpret as plausible indicators of organizational quality (Connelly et al., 2010, 2024). In this process, SMM does not only communicate, but also magnifies and strengthens brand signals, making them easier to translate into positive organizational judgments. This increases cognitive access and decreases evaluative uncertainty, which allows more confident stakeholder judgments. Notably, this process builds upon signaling theory by showing that signals are not simply relayed but are algorithmically boosted and socially verified in digital ecosystems, enhancing their interpretive salience, However, the success of these signals is based on their visibility, interactivity, and perceived authenticity, implying that brand image might not be enough without successful digital amplification. This mediating position is especially important in the context of recruitment, where exposure to social media content increases both symbolic and instrumental employer brand associations, making organizations more attractive (Carpentier et al., 2017; El-Menawy & Saleh, 2023; Kissel & Büttgen, 2015), Digital transformation in the Iraqi banking industry, where economic instability, digital transformation, and talent competition are the main factors, digital transformation is central to conveying and enhancing brand image messages, allowing banks to stand out and recruit high-quality applicants (Al-Hachami & Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022), Based on this, social media marketing is re-conceptualized not as a communication tool, but as a capability-based signal amplification process that transforms latent brand image attributes into salient, credible, and cognitively accessible organizational perceptions. H4: Social media marketing mediates the positive relationship between brand image and organizational attractiveness in the Iraqi banking sector. 3. Methodology The research design of the study is a quantitative, cross-sectional study that will rigorously investigate the relationship between brand image, social media marketing (SMM), and organizational attractiveness in the Iraqi banking industry (Al-Hachami and Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022). The cross-sectional method is suitable in exploring theoretically based relationships between latent constructs, especially in digitally mediated settings where perceptual constructs are relatively stable over time. Although causal inferences are viewed with a grain of salt, this design is still popular in marketing and organization studies (Hair et al., 2021), The empirical setting includes the employees and managerial personnel of the Iraqi banks that are actively involved in digital financial services and social media communication. The unit of analysis is the individual respondent. The sample was recruited based on a non-probability purposive sampling method via professional networks and online platforms because of access limitations, and because of contextual relevance (Al-Hachami & Alameri, 2022; Nwanebo, 2025). The number of respondents (357) was sufficient to meet minimum sample size requirements of PLS-SEM and provide sufficient statistical power (Hair et al., 2021), A structured electronic questionnaire was used to gather data in a period of four months. To increase the consistency and interpretability of responses, a five-point Likert scale (1 strongly disagree, 5 strongly agree) was used. The involvement was voluntary, anonymity and confidentiality were guaranteed, and no personally identifiable data were gathered in accordance with the ethical research principles, Multi-item scales based on previous validated studies were operationalised and adapted to the digital banking context to construct all constructs (Althuwaini, 2022; Laradi et al., 2023; Thang and Trang, 2024). The measurement of brand image was conducted with four items that included organizational reputation, prestige, trustworthiness, and familiarity (Thang and Trang, 2024). Eight items were operationalised to reflect informativeness, interaction (social presence), entertainment, and trendiness to operationalise social media marketing (Carpentier et al., 2017, 2019; Kissel and Buettgen, 2015). The attractiveness of organizations was assessed with the help of sixteen items that reflected the instrumental and symbolic values, such as economic, social, development, and application value dimensions (Carpentier et al., 2017, 2019; Jayasinghe, 2018). The constructs were all conceptualised as reflective, which is in line with previous studies and theoretical conceptualisation. Table 1 shows measurement details, Measurement model was evaluated based on indicator loadings, composite reliability (CR), rho A and average variance extracted (AVE). The heterotrait-monotrait (HTMT) ratio was used to assess discriminant validity, and all the values were lower than the recommended values (Hair et al., 2021). The variance inflation factor (VIF) was used to measure multicollinearity, and all the values were less than 3.3, Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyze the data with SmartPLS 4.0, which is suitable in prediction-oriented studies, mediation analysis, and multifaceted latent models. PLS-SEM is also resistant to the breach of multivariate normality, which is verified by skewness, kurtosis, and the test of Mardia (Hair et al., 2021). Bootstrapping with 5,000 resamples was used to assess statistical significance of direct and indirect effects. This methodology is consistent with the aim of the study to create a prediction-based and capability-driven explanation of organizational performance in digitally mediated settings, Procedural remedies were applied to overcome common method bias, such as assurance of anonymity and design of questionnaires. Harman single-factor test statistically revealed no dominant factor, with full collinearity VIF values less than 3.3 (Kock, 2015), The non-response bias was evaluated by comparing the early and late respondents and no significant differences were found (Groves and Peytcheva, 2008). The Gaussian copula method was used to test endogeneity, and there was no significant impact on the estimated relationships (Hult et al., 2018). Additional robustness tests were done to guarantee the stability and consistency of the results. Table 1 Measurement Scales and Construct Operationalization Construct Source(s) Dimensions / Sub-scales No. of Items Sample Item(s) Brand Image Thắng & Trang (2024) Reputation, Prestige, Trustworthiness, Familiarity 4 “I have heard many good things about this company.” Social Media Marketing Carpentier et al. (2017, 2019); Kissel & Büttgen (2015) Informativeness, Interaction, Entertainment, Trendiness 8 “The organization’s social media provides useful information.” Organizational Attractiveness Berthon et al.; Jayasinghe (2018) Economic, Social, Development, Application Value 16 “This organization offers good career opportunities.” 4. Results 4.1 Descriptive Statistics To examine the distributional properties of the study variables, the descriptive statistics were computed at construct and dimensional levels. As shown in Table 2 , brand image, social media marketing (SMM), and organizational attractiveness have mean values that are above the scale midpoint, which suggests that there is an overall inclination towards consensus among respondents in the existence of positive organizational perceptions and digital engagement practices. The highest of the study constructs in terms of the means of social media marketing is the aggregate level, followed by organizational attractiveness and brand image, which illustrates the centrality of digital interaction in the development of stakeholder perceptions, At the dimensional level, brand image has high mean values in all its elements, especially in reputation and trustworthiness, which show high perceptions of organizational credibility among the respondents. The dimensions of social media marketing show variability with informativeness and interaction (social presence) reporting the highest mean values, which indicates that the signaling environment is characterized by information richness and interactive visibility, and the values of entertainment and trendiness are relatively moderate, In the same vein, the dimensions of organizational attractiveness show that the economic and development value dimensions have a relatively higher mean score, then social and application value, which shows the significance of both instrumental and symbolic benefits in determining organizational attractiveness. The values of standard deviation show that there is a moderate dispersion of all constructs, which implies that there is a reasonable variability in responses, Moreover, the skewness and kurtosis values are within acceptable limits (skewness of ± 2 and kurtosis of ± 7), which proves that there is no extreme non-normality and the data can be used to model the variance-based structural equation and test the hypothesis. Table 2 Descriptive Statistics Construct Dimension Mean SD Skewness Kurtosis Brand Image Reputation 4.08 0.58 -0.95 1.85 Prestige 4.05 0.60 -0.90 1.80 Trustworthiness 4.10 0.55 -1.00 1.95 Familiarity 3.98 0.62 -0.85 1.70 Social Media Marketing Informativeness 4.12 0.56 -1.02 2.00 Interaction (Social Presence) 4.08 0.58 -0.98 1.90 Entertainment 3.90 0.63 -0.85 1.70 Trendiness 3.88 0.65 -0.80 1.60 Organizational Attractiveness Economic Value 4.10 0.57 -1.00 2.05 Development Value 4.07 0.58 -0.95 1.90 Social Value 3.95 0.61 -0.88 1.75 Application Value 3.92 0.63 -0.85 1.70 Note : All values fall within acceptable normality thresholds. 4.2 Reliability and Validity The measurement model was evaluated in accordance with the guidelines of PLS-SEM (Hair et al., 2021), assessing the reliability of indicators, internal consistency, convergent validity, discriminant validity, and collinearity of the reflective measurement model. Although all indicators are within the recommended thresholds, there are slight differences in outer loadings, which are within acceptable limits and do not influence construct validity. Table 3 Measurement Model Assessment Construct Items (n) Cronbach’s Alpha rho_A Composite Reliability (CR) AVE Brand Image (BI) 4 0.88 0.89 0.91 0.72 Social Media Marketing (SMM) 8 0.92 0.93 0.94 0.66 Organizational Attractiveness (OA) 16 0.93 0.94 0.95 0.64 Internal consistency reliability and convergent validity are achieved, with the values of Cronbach alpha, rho A, and composite reliability being above the recommended value of 0.70, and the average variance extracted being above 0.50 (Hair et al., 2021). These findings affirm that the constructs have high internal consistency and reasonable convergent validity. Table 4 Discriminant Validity (HTMT) Construct BI SMM OA Brand Image (BI) — Social Media Marketing (SMM) 0.78 — Organizational Attractiveness (OA) 0.74 0.82 — The heterotraitmonotrait ratio (HTMT) was used to measure discriminant validity because it is more sensitive in identifying the absence of discriminant validity. The values of all HTMT are less than the conservative value of 0.85 and the bootstrapped confidence intervals do not include 1, which proves that there is sufficient discriminant validity and conceptual distinction between constructs. Table 5 Outer Loadings and Measurement VIF Construct Item Range Loading Range VIF Range Brand Image (BI) BI1 – BI4 0.76–0.88 1.70–2.30 Social Media Marketing (SMM) SMM1 – SMM8 0.74–0.89 1.80–2.60 Organizational Attractiveness (OA) OA1 – OA16 0.75–0.88 1.70–2.40 Outer loadings were used to determine indicator reliability. The indicators are loaded on their constructs (≥ 0.70), which proves sufficient indicator reliability (Hair et al., 2021). The level of multicollinearity was tested at the measurement level through variance inflation factors (VIF), and all the values were less than the conservative level of 3.3, which means that there are no collinearity issues. Table 6 Full Collinearity Assessment Construct Full VIF Brand Image (BI) 2.10 Social Media Marketing (SMM) 2.30 Organizational Attractiveness (OA) 2.25 Full collinearity VIF values were also analyzed to further evaluate the possibility of endogeneity and common method bias. All the values are less than 3.3, which further confirms that the model does not have any pathological collinearity or endogeneity issues (Kock, 2017), The measurement model shows a high level of reliability and validity in all the evaluation criteria as shown in Tables 3 – 6 . The internal consistency and convergent validity are well established, and all constructs are above the recommended levels, Strong outer loadings confirm indicator reliability, whereas the values of VIF at the measurement level demonstrate that the issue of multicollinearity is not a concern. The HTMT ratios below the conservative level support discriminant validity, which guarantees a clear conceptual differentiation between constructs, Moreover, the complete evaluation of collinearity proves that there are no endogeneity problems, which strengthens the validity of the measurement model. Taken together, these findings give a solid empirical evidence that the constructs are theoretically based, statistically sound and empirically different, thus giving a solid and theoretically consistent base to the further estimation of the structural model. 4.3 Structural Model Assessment The structural model was tested to test the hypothesized relationships between brand image, social media marketing (SMM), and organizational attractiveness through regression-based estimates in line with PLS-SEM interpretation logic. Table 7 Structural Model Results with Confidence Intervals Hypothesis Relationship β t-value p-value 95% CI Result H1 BI → OA 0.42 7.85 < 0.001 [0.31, 0.52] Supported H2 SMM → BI 0.63 12.10 < 0.001 [0.54, 0.71] Supported H3 SMM → OA 0.48 8.92 < 0.001 [0.37, 0.59] Supported H4 BI → SMM → OA 0.30 6.75 < 0.001 [0.21, 0.40] Supported The findings are very empirical in supporting all hypotheses proposed. In particular, H1, H2, and H3 are accepted, which means that brand image and social media marketing have strong positive impacts on organizational attractiveness, and social media marketing has a strong positive impact on brand image. These results affirm the inter-relationship between branding and online interaction in the development of organizational attractiveness, Regarding the magnitude of the effect, social media marketing has a significant and statistically significant influence on brand image ( 0.63), which indicates its importance as a key factor in brand perception formation in the digital space. Moreover, SMM has a significant direct effect on organizational attractiveness (= 0.48), which implies that digitally mediated relationships are essential in influencing stakeholders in their evaluations, The fact that brand image has a positive influence on organizational attractiveness ( 0.42) is also important, which confirms the notion that brand image is a basic signaling system that organizations rely on to project prestige, credibility, and value to prospective employees, Moreover, the mediation analysis (H4) indicates that there is a strong indirect impact of brand image on organizational attractiveness via social media marketing (= 0.30), which proves that SMM is a major transmission channel that transforms latent brand attributes into visible and evaluative digital cues. This observation confirms the theoretical claim that digital platforms do not simply relay but enhance and operationalize brand signals in digitally mediated spaces. 4.4 Coefficient of Determination, Predictive Relevance, Effect Size, and PLSpredict The coefficient of determination (R 2 ), predictive relevance (Q 2 ), effect size (f 2 ), and out-of-sample predictive performance through PLSpredict were used to evaluate the explanatory power, predictive relevance, and relative importance of the structural relationships as shown in Tables 8 – 10 . Table 8 Coefficient of Determination (R²) and Predictive Relevance (Q²) Endogenous Construct R² Q² Brand Image (BI) 0.40 0.25 Organizational Attractiveness (OA) 0.52 0.34 Table 9 Effect Size (f²) Relationship f² Effect Size SMM → BI 0.48 Large BI → OA 0.14 Small SMM → OA 0.20 Medium Table 10 PLSpredict Results Indicator RMSE (PLS) RMSE (LM) Result OA1 Lower Higher Predictive OA2 Lower Higher Predictive OA3 Lower Higher Predictive The findings show that the model accounts 40 percent of the variance in brand image and 52 percent in organizational attractiveness, which is moderate explanatory power in line with the set standards. This degree of explanatory power is deemed to be strong in the context of marketing and organizational research, where the constructs of perception and behavior are complex in nature and affected by various factors (Hair et al., 2021). Moreover, all the Q2 values are greater than zero, which proves that the model has sufficient predictive relevance and can produce meaningful in-sample predictions, In addition to explanatory power, effect size analysis gives a more in-depth understanding of the relative contribution of each structural relationship. The social media marketing has a significant impact on brand image (f 2 = 0.48), which highlights its key position as one of the key factors in the formation of brand perception in the digital world. Conversely, the direct influence of brand image on organizational attractiveness is relatively low (f 2 = 0.14), which implies that brand-related perceptions might not be enough to completely influence stakeholder judgments, The social media marketing shows a moderate impact on the attractiveness of the organization (f 2 = 0.20), which indicates that it is one of the primary ways in which the digital interaction can be converted into organizational attractiveness. This implies that SMM is not just a channel of communication but a dynamic perception-making force, Notably, the results of the PLSpredict model give further indications of the predictive validity of the model. The PLS-SEM estimates are better than the linear model benchmark (LM) in all indicators, as shown by reduced RMSE values. The majority of indicators indicate lower values of RMSE than the LM benchmark, which proves that the model has a better out-of-sample predictive power, which can be applied to predictive models, not only to explanatory modeling, Taken together, these results indicate a signal amplification viewpoint, according to which the effect of brand image on organizational attractiveness is partially mediated and enhanced by social media marketing. This supports the conceptualization of SMM as a capability-based process that transforms latent brand attributes into visible, decipherable, and impactful digital cues in the context of recruitment and stakeholder assessment. 4.5 Mediation Analysis The mediation analysis is an extension of the structural model that demonstrates that the relationship between brand image and organizational attractiveness is mediated by social media marketing (SMM) to some extent. The indirect influence is so high that SMM is worth considering as one of the most important processes that transform the perceptions of the brand into positive organizational judgments, This observation is in line with the signaling theory that states that the usefulness of signals is not only a question of their presence but also their visibility, interpretability, and credibility. In this regard, social media marketing can be viewed as a signal amplification process that converts latent brand image attributes into visible and interactive digital signals, thus increasing their influence on the stakeholders in terms of their judgments, The findings show that brand image has a direct positive impact on organizational attractiveness, but its impact is enhanced by social media marketing. This trend indicates that social media marketing is partially mediated, i.e. it does not replace the direct impact of brand image. This implies that brand image might not be enough to influence the perceptions of the stakeholders to the full extent unless it is well communicated and reinforced using digital platforms, A deeper analysis of the indirect effect shows that the organizations that use social media marketing are better at transforming positive brand perceptions into increased organizational appeal. Conversely, when there is no robust digital interaction, the effect of brand image is relatively weakened, which means that the conversion of brand cues into evaluative results is conditional on digital amplification processes. The magnitude of the indirect effect also highlights the pivotal role of digitally mediated interactions in influencing stakeholder assessments, Notably, the mediation effect is significant, but the data is cross-sectional, which requires care in causal interpretation. Based on this, the results are to be interpreted as reflective of underlying processes and not causal relationships, In general, the findings contribute to a mechanism-based approach, which makes social media marketing a capability-based signal amplification channel where brand image is converted into organizational attractiveness in digital and high-uncertainty settings, In order to guarantee the stability and validity of the estimated relationships, and to deal with the possible issues of model misspecification, multicollinearity, and endogeneity, a set of robustness checks were performed, as indicated in Table 11 , In particular, the results of multicollinearity diagnostics show that all the values of the variance inflation factor (VIF) are lower than the conservative value of 3.3, which proves that there are no collinearity issues between the constructs of predictors. Moreover, another model specification, which reversed the direction of the key relationships (e.g., the reverse effect of organizational attractiveness on social media marketing), had less explanatory power than the proposed model, which is another empirical evidence of its superiority and theoretical consistency, In addition, bootstrapping findings indicate that the parameter estimates are consistent and the significance levels are consistent across resamples, which supports the accuracy and consistency of the results. The full collinearity test also shows that there is no indication of endogeneity problems, which implies that the estimated relationships are not likely to be systematically biased, Overall, these robustness checks are a positive sign that the model is stable, methodologically sound, and not sensitive to other specifications, which enhances the belief in the validity and generalizability of the study results. Table 11 Robustness Checks Summary Robustness Test Key Result Interpretation Multicollinearity (VIF) All values < 3.3 Indicates absence of collinearity concerns among predictor constructs Alternative Model Specification Lower explanatory power Supports the superiority and theoretical coherence of the proposed model Bootstrapping Stability Stable estimates with consistent significance Confirms precision and reliability of parameter estimates across resamples Endogeneity (Full Collinearity VIF) No issues detected Suggests absence of severe endogeneity and unbiased estimations The robustness checks are continuously performed to make sure that the model is stable, reliable, and not sensitive to other specifications, which enhances the credibility, robustness, and generalizability of the empirical findings. 5. Discussion The results of this research offer strong empirical evidence and resolve a significant conflict between the conventional branding rationales and digitally mediated stakeholder perceptions. In particular, although brand image has traditionally been defined as a fixed and internally controlled resource, the findings show that its influence on organizational attractiveness is becoming more and more dependent on the effectiveness with which it is stimulated and enhanced by digital engagement processes. This redefines branding as a dynamic, interaction-based process, and provides a better understanding of how brand image, social media marketing (SMM), and organizational attractiveness interact, The validation of Hypothesis 1 supports the importance of brand image as a major contributor to organizational attractiveness, which is consistent with previous studies that highlight its impact on stakeholder perceptions and employer branding outcomes (Hair et al., 2018; Santiago and Tiago, 2025; Sivertzen et al., 2013; Thang and Trang, 2024). Nevertheless, in addition to affirming this relationship, the results indicate that brand image alone cannot be effective in digitally mediated settings unless it is constantly converted into visible and interactive cues, In the same vein, Hypothesis 2 emphasizes the strong influence of social media marketing on brand image, showing that digitally mediated interactions do not just convey brand attributes but actually create and co-construct them in real time (Marquez-Oyakawa et al., 2025). This means that the one-way brand communication will be changed to a more participatory and platform-based branding logic, Hypothesis 3 further confirms the pivotal role of social media marketing in enhancing organizational attractiveness, consistent with prior studies on digital marketing and employer branding (El-Menawy & Saleh, 2023; Sivertzen et al., 2013). More to the point, this association emphasizes the fact that attractiveness is no longer produced by organizational messaging per se, but by continuous digital interactions that signify credibility, transparency, and quality of interaction, Notably, the results support Hypothesis 4, since they establish the mediating role of social media marketing, implying that the relationship between brand image and organizational attractiveness is mediated by digitally mediated engagement. This observation demonstrates a more profound process: social media marketing is not just a channel of transmission but a process of transformation that transforms latent brand qualities into visible and evaluative cues (Bahri-Ammari et al., 2022; Kissel and Buettgen, 2015; Thang and Trang, 2024), More to the point, these results demonstrate a basic contradiction in the modern branding studies: as much as organizations invest a lot of money in creating a good brand image, the success of these investments is determined by how well they can translate the images into dynamic, digitally mediated experiences. This makes it difficult to adhere to the traditional assumptions that brand image leads to positive outcomes directly, and the value realization in the digital environment is contingent and process-based, In addition to the structural relationships, the model has a high level of explanatory power and predictive relevance, which supports its empirical validity and out-of-sample predictive ability (Hair et al., 2018, 2021; Shmueli et al., 2019). The study is methodologically rigorous, as it handles the possible endogeneity and collinearity issues with full collinearity tests (Hult et al., 2018; Kock, 2015, 2017). It is important to note that the methodological approach supports a prediction-based conception of the impact of digitally mediated capabilities on organizational outcomes, which is not within the explanatory models. Theoretically, this study adds to the employer branding and signaling theory by rebranding social media marketing as a signal amplification mechanism founded on capabilities rather than a communication tool. This reframing transforms the view of digital marketing as a passive channel to an active mechanism that operationalizes and strengthens brand-related cues in digitally mediated situations. In a broader sense, it adds to the new discussions of value construction and perception in digital ecosystems, where visibility, interaction, and responsiveness are the key aspects of organizational assessment. The managerial implications of the results are that organizations are no longer to be passive in brand-building efforts but rather actively organize digital engagement strategies that continuously reaffirm and translate brand attributes into observable cues. This means that in competitive talent markets, organizational attractiveness is becoming more and more determined by the capacity of the firm to have a stable and interactive digital presence. In this way, employer branding competitive advantage is no longer based on what organizations are, but on how well they communicate and implement their identity in the digital realm, these contributions, the study has some limitations. The cross-sectional design limits causal inference, and the use of self-reported data could lead to potential bias, but procedural remedies and robustness checks were used to address these issues (Kock, 2015, 2017). It is suggested that future research must take into account longitudinal designs or multi-source data to further validate the proposed relationships and explore their time dynamics across different sectors and digitally transforming settings, By overcoming these constraints, future studies will be able to create a more causally based and strategically applicable concept of how digitally mediated engagement can convert organizational value into long-term competitive advantage. 6. Conclusion Overall, the current research offers strong and theoretically supported empirical data that brand image contributes to organizational attractiveness to a considerable extent, and social media marketing is an essential mediating variable. This correlation was strictly tested and validated with the help of partial least squares structural equation modeling, which proved a significant explanatory power and predictive relevance (Hair et al., 2018, 2021; Shmueli et al., 2019), The effect size analysis also highlighted the high impact of brand image on social media marketing, and the mediation findings show that the effect of brand image on organizational attractiveness is greatly enhanced by digitally mediated engagement. These results emphasize that brand image effectiveness is not achieved to its full extent in isolation but is enhanced by interactions through social media, This study contributes to theoretical knowledge by redefining social media marketing as a signal amplification mechanism based on capabilities within the signaling and employer branding theories, as opposed to conventional views. In particular, it transforms digital marketing into an active mechanism that operationalizes and reinforces brand-related cues in interactive online spaces, thus influencing the perceptions of stakeholders more effectively (Bahri-Ammari et al., 2022; Carpentier et al., 2019; Confetto et al., 2023; Kissel and Buettgen, 2015; Santiago and This view is consistent with the new studies that focus on the importance of social media in communicating employer brand qualities like competence and warmth, which increase organizational appeal and job seeker intentions (Carpentier et al., 2019; Suprawan et al., 2025) At the managerial level, organizations are encouraged to combine strategic social media activities to enhance brand signals, especially in competitive talent markets where interactive digital presence is paramount (Carpentier et al., 2019; El-Menawy and Saleh, 2023; Marquez-Oyakawa et al., 2025). This involves creating content that is more socially present and informative, capitalizing on user-generated content, and promoting real-time engagement to build employer brand equity and attract high-quality talent, especially digitally oriented generations like Generation Z (El-Menawy and Saleh, 2023; Santiago and Tiago, 2025; Suprawan et al., 2025; Laradi et al., 20 This management implication supports the main conflict between fixed brand perceptions and moving digital amplification processes, In spite of these contributions, the study has some limitations. The cross-sectional nature limits causal inference, and the use of self-reported data can introduce residual bias, but robustness checks of endogeneity, collinearity, and common method bias were performed (Hult et al., 2018; Kock, 2015, 2017; Silva and Dias, 2022). It is recommended that future studies consider longitudinal and multi-source designs to study the temporal dynamics across sectors and digitally changing contexts, possibly with experimental designs and a variety of generational cohorts to increase generalizability (Hanu et al., 2021; Jasim et al., 2026; Stadler et al., 2025; Thang and Trang, 2024), Finally, this paper shows that in digitally mediated settings, the attractiveness of organizations is no longer defined by what companies say, but by how well they modify and enhance brand messages by means of interactive digital interaction. 6. Managerial Implications This research has important strategic implications to banking executives in an ever-digitized and talent-competitive world. First, the findings indicate that brand image is no longer enough to make organizations more attractive unless it is actively converted into visible and credible cues. This means that managers must no longer be content with the old-fashioned reputation-building activities but rather plan to have integrated communication capabilities that constantly project organizational values, credibility, and employer quality via platform-based communication. Second, social media marketing is not only a promotional tool but a strategic capability that allows banks to enhance brand-related cues and proactively influence stakeholder perceptions in real time. Based on this, managers are advised to use interactive, data-driven, and authentic social media functions to promote career opportunities, organizational culture, employee value propositions, and institutional stability in a way that engagement is meaningful and strategically aligned with employer branding goals. Third, the mediating effect of social media marketing suggests that the attractiveness of organizations is enhanced when positive brand perceptions are successfully converted into visible online experiences. This demands greater cross-functional coordination and integration of marketing, human resource management, and corporate communication functions, which will allow the transmission of signals across all touchpoints in a consistent and coherent manner. Lastly, in unstable and information-scarce settings like the Iraqi banking industry, managers ought to understand that potential employees are becoming more and more critical of organizations in terms of visible indicators, as opposed to reputational assertions. The inability to have an active, credible, and responsive online presence can seriously undermine the attractiveness of the employer and destroy competitive positioning. 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International Journal of Organizational Analysis , 31 (8), 1. https://doi.org/10.1108/ijoa-01-2022-3129 Sivertzen, A.-M., Nilsen, E. R., & Olafsen, A. H. (2013). Employer branding: employer attractiveness and the use of social media. Journal of Product & Brand Management , 22 (7), 473. https://doi.org/10.1108/jpbm-09-2013-0393 Stadler, R., Fecker, D., & Huber, L. (2025). Co-branding alliances as an employer branding strategy. Journal of Hospitality and Tourism Insights , 8 (11), 259. https://doi.org/10.1108/jhti-03-2025-0358 Suprawan, L., Suengkamolpisut, W., & Singhatong, S. (2025). The impact of social media characteristics on young job applicants’ intentions: mediating roles of employer brand attractiveness and person-organization fit. International Studies of Management and Organization , 1. https://doi.org/10.1080/00208825.2025.2500831 Tahir, A. H., Adnan, M., & Saeed, Z. (2024). The impact of brand image on customer satisfaction and brand loyalty: A systematic literature review. Heliyon , 10 (16). https://doi.org/10.1016/j.heliyon.2024.e36254 Taj, S. A. (2016). Application of signaling theory in management research: Addressing major gaps in theory. European Management Journal , 34 (4), 338. https://doi.org/10.1016/j.emj.2016.02.001 Tarabieh, S. (2022). The Impact of Social-media Marketing Activities on Consumers’ Loyalty Intentions: The Mediating Roles of Brand Awareness, Consumer Brand Engagement and Brand Image. Jordan Journal of Business Administration , 18 (4). https://doi.org/10.35516/jjba.v18i4.455 Thắng, N. N., & Trang, P. T. (2024). Employer branding, organization’s image and reputation, and intention to apply: the moderating role of the availability of organizational information on social media. Frontiers in Sociology , 9 . https://doi.org/10.3389/fsoc.2024.1256733 Tumasjan, A., Kunze, F., Bruch, H., & Welpe, I. M. (2019). Linking employer branding orientation and firm performance: Testing a dual mediation route of recruitment efficiency and positive affective climate. Human Resource Management , 59 (1), 83. https://doi.org/10.1002/hrm.21980 Türker, N., & Üngüren, E. (2025). Digital footprints and recruitment: an experimental study on the impact of social media content on hiring decisions. Frontiers in Psychology , 16 . https://doi.org/10.3389/fpsyg.2025.1693850 Turki, M. D., & Sabbar, M. (2023). Studying the Role of Banking Marketing in Supporting the Competitive Advantage of the Iraqi Banks. International Journal of Professional Business Review , 8 (4). https://doi.org/10.26668/businessreview/2023.v8i4.1342 Vives, X. (2019). Digital Disruption in Banking. Annual Review of Financial Economics , 11 (1), 243. https://doi.org/10.1146/annurev-financial-100719-120854 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 06 May, 2026 Editor assigned by journal 06 May, 2026 Submission checks completed at journal 06 May, 2026 First submitted to journal 04 May, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9612378","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638802730,"identity":"ee9d9b9a-b1ba-4d85-bcc7-48583950ceed","order_by":0,"name":"Hawraa Mushtaq Talib","email":"data:image/png;base64,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","orcid":"","institution":"University of Baghdad","correspondingAuthor":true,"prefix":"","firstName":"Hawraa","middleName":"Mushtaq","lastName":"Talib","suffix":""},{"id":638802731,"identity":"7510fd86-60d3-4785-9eab-2b66070203c9","order_by":1,"name":"Sarah Ali Saeed Alameri","email":"","orcid":"","institution":"University of Baghdad","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"Ali Saeed","lastName":"Alameri","suffix":""}],"badges":[],"createdAt":"2026-05-04 22:39:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9612378/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9612378/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109269253,"identity":"fd045d05-7216-4cb5-929b-4392f717417a","added_by":"auto","created_at":"2026-05-14 13:27:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53496,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9612378/v1/765f2fdf96bc70f46c72b4cb.png"},{"id":109269258,"identity":"d0fa99e3-8e00-4702-978d-6b15dac21543","added_by":"auto","created_at":"2026-05-14 13:27:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":412268,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9612378/v1/d9396b68-31de-45a3-a7ce-bd883b772b59.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Effect of Brand Image on Organizational Attractiveness: The Mediating Role of Social Media Marketing in the Banking Sector","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAlthough banks have traditionally used stable reputations over decades to instill trust in stakeholders in high-risk settings, the real-time interactivity of social media allows building or destroying brand equity in a short period of time, disrupting the conventional dynamics of trust (Althuwaini, 2022; Bernini et al., 2021; Vives, 2019). This is especially acute in the emerging markets like the banking sector in Iraq, where the digital transformation is gaining momentum in the face of economic instability, regulatory limitations, and talent shortages, making the organizational attractiveness a key factor in recruitment, retention, and competitive positioning (Alameri et al., 2024; Husseini, 2025; Jasim et al., 2026; Mado et al., 2025), Current studies assume brand image as a direct precursor of organizational attractiveness (Shahid and Ayyaz, 2023) and discuss the results of social media marketing (SMM) in terms of customer loyalty and employer branding (Salhab et al., 2023; El-Menawy and Saleh, 2023; Marquez-Oyakawa et al., 2025). Nevertheless, this literature is still theoretically disjointed. Previous research is mostly on direct effects or downstream outcomes, without integrative frameworks that describe the mechanisms between these constructs. As a result, there is still a critical gap in the literature, with studies not considering the role of SMM in mediating the transfer of brand image to organizational attractiveness in digitally disrupted banking contexts, as well as in under-researched emerging economies where information asymmetries are more pronounced., More to the point, this restriction inhibits the development of theory by obscuring the operationalization of intangible brand assets into stakeholder-based outcomes via digitally mediated processes. This poses a theoretical conflict between the symbolic quality of brand image and the visible processes needed to shape stakeholder perceptions in digital spaces. The disjuncture is particularly acute in the banking sector that is rapidly digitalizing and becoming more dependent on online platforms to influence customer interactions and brand perceptions (Al-Rdaydeh et al., 2025), where the process of symbolic brand value being transformed into visible stakeholder reactions is under-theorizedm In order to fill this gap, this paper will look at the mediating effect of social media marketing in the correlation between brand image and organizational attractiveness in the Iraqi banking industry. Based on the signaling theory, SMM is theorized as a system of visible digital cues that communicate latent brand qualities like credibility, reliability, and organizational values- to external stakeholders. Such signals decrease uncertainty and alleviate information asymmetries by converting abstract brand perceptions into tangible, interactive, and publicly verifiable signals, which increase organizational appeal (Carpentier et al., 2019; Thang and Trang, 2024).\u003c/p\u003e \u003cp\u003eThis study theoretically redefines social media marketing as a capability-based mediator that connects intangible brand resources to organizational attractiveness outcomes (Hafez, 2022; Laradi et al., 2023). By so doing, it builds upon previous studies that have largely concentrated on direct relationships or downstream effects like purchase intention and brand awareness (Bibi et al., 2025; Tarabieh, 2022), by elucidating the mediating processes between brand image and organizational-level implications, Contextually, the study is relevant as it places these mechanisms in the context of the Iraqi banking industry, which is a little-researched emerging market with institutional volatility, pressures of digital transformation, and changing stakeholder expectations. This background is especially pertinent in the light of the recent developments in strategic intelligence, the use of fintech, sustainability plans, knowledge management, organizational agility, and AI-based practices in banking (Al-Ameri et al., 2023; Almado \u0026amp; Algburi, 2025; Alameri et al., 2024; Saleh \u0026amp; Alameri, 2022; Salman et al., 2019; Mado et al., 2025)m Although the role of social media marketing in influencing stakeholder engagement is increasingly becoming significant, there is a paucity of empirical research investigating its mediating effect between brand image and organizational attractiveness specifically in the banking sector in developing economies (Hafez, 2022; Marquez-Oyakawa et al., 2025; ONUORAH et al., 2022; Shahid and To this end, the paper will utilize a strict mediation model to deconstruct the mediating processes between these constructions to offer a subtle insight into how social media use can be converted into organizational benefits in unstable and information-scarce contexts, In this way, this research contributes to a signaling-based account of how digitally mediated interactions transform intangible brand assets into tangible organizational outcomes in uncertain conditions.\u003c/p\u003e"},{"header":"2. Conceptual and Theoretical Foundation","content":"\u003cp\u003eBrand image refers to the perceptions and mental associations of consumers or stakeholders with a brand, including tangible and intangible attributes that help to differentiate and create value (Korchia, 1999; Laradi et al., 2023; Tahir et al., 2024). Strategically, it is a vital intangible resource that influences stakeholder assessments and organizational positioning. Social media marketing (SMM), in turn, refers to the strategic use of digital platforms to engage customers and partners through activities such as entertainment, interaction, and trendiness, with the aim of enhancing brand awareness and fostering long-term relationships (Althuwaini, 2022; Laradi et al., 2023; Lilembalemba \u0026amp; Phiri, 2024). Organizational attractiveness refers to the perceived gains of being part of an organization, such as economic, developmental, and symbolic values like prestige and innovation (Dassler et al., 2022; El-Menawy \u0026amp; Saleh, 2023; Santiago \u0026amp; Tiago, 2025; Shahid \u0026amp; Ayyaz, 2023), Signaling theory, first formulated by Spence, deals with information asymmetry, where one party has better information about its quality than the receiver. To lessen this asymmetry, organizations send observable signals that provide credible information regarding latent characteristics. Low-quality signalers tend to be more expensive to provide effective signals, whereas high-quality signalers are cheaper to provide effective signals, which is a guarantee of reliability (Confetto et al., 2023; Connelly et al., 2010, 2024; Taj, 2016). Signaling theory is used in marketing and recruitment settings to describe how organizations use digital activities to convey credibility, minimize uncertainty, and increase trust among stakeholders (Carpentier et al., 2019; Thắng and Trang, 2024; T\u0026uuml;rker and \u0026Uuml;nguren, 2025). But in digitally mediated spaces, signals are not simply sent, but are algorithmically edited, enhanced, and socially approved, changing their visibility, credibility, and interpretive effect, It is based on this view that this paper develops a signaling-based architecture where brand image is theorized as a latent signal aggregation construct that represents underlying organizational quality and values, and social media marketing is a capability-based signaling infrastructure that converts, amplifies, and broadcasts these signals into visible and interactive digital signals. By using SMM, organizations are actively involved in the construction, prioritization, and interpretation of signals in digital ecosystems, making them more cognitively accessible, less ambiguous, and allowing stakeholders to make more coherent judgments, The attractiveness of an organization is thus determined as the outcome of the cognitive evaluation of the stakeholders of these digitally mediated cues, particularly in cases of uncertainty. This process is particularly relevant in emerging economies like Iraq, where economic instability and institutional insecurity increase the dependence on visible digital indicators (Carpentier et al., 2019; Confetto et al., 2023; Laradi et al., 2023; Suprawan et al., 2025; Thắng \u0026amp; Trang, 2024), Based on this, this paper redefines social media marketing as not just a communication medium, but as a key signaling infrastructure that regulates the process of brand image into organizational appeal, which offers a single theoretical basis to the proposed relationships.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Brand Image and Organizational Attractiveness\u003c/h2\u003e \u003cp\u003eA strong brand image is a key factor that increases the attractiveness of the organization because it influences the perceptions of the stakeholders regarding the prestige, reputation, and overall value of the organization as an employer (Dassler et al., 2022; Davies et al., 2024; El-Menawy and Saleh, 2023; Santiago and Tiago, 2025). Empirical data always confirms that positive brand image perceptions have a positive impact on the assessment of potential employees, thus increasing organizational attractiveness in both instrumental (e.g., economic and developmental benefits) and symbolic (e.g., prestige and innovation) aspects (Erdil and Tatar, 2019; Santiago and Tiago, 2025; Shahid and Ayyaz, 2023)m Grounded in signaling theory, brand image is a high-level, aggregated cue that communicates organizational quality, credibility, and distinctiveness, thus decreasing information asymmetry between organizations and job seekers (Connelly et al., 2010; Davies et al., 2024; Heilmann et al., 2022). In contrast to discrete communication signals, brand image is a cumulative evaluative construct that combines various organizational cues into a consistent perception, which allows stakeholders to make holistic judgments in the face of uncertainty. This enhances cognitive fluency and reduces evaluative ambiguity thereby facilitating easier and more positive and confident judgments of organizational attractiveness, The success of such a relationship, though, is determined by the clarity, consistency and credibility of the underlying signals that constitute brand image, which means that not all brand images are equally converted into attractiveness. In the framework of the Iraqi banking sector, where the economy is unstable, and the digital transformation is an ongoing process, it is a strategic requirement to create a strong and consistent brand image to make the organization more appealing and recruit high-quality talent (Nwanebo, 2025; Thắng \u0026amp; Trang, 2024), Brand image is thus redefined not as a perceptual result, but as a strategic signal aggregation process that influences the cognitive processing and assessment of organizational value by potential employees.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1: Brand image positively influences organizational attractiveness by enhancing the cognitive evaluation and perceived credibility of employer-related signals.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Brand Image and Social Media Marketing\u003c/h2\u003e \u003cp\u003eSocial media marketing can greatly improve brand image by spreading visible cues that communicate organizational prestige, innovation, and trustworthiness to stakeholders, especially potential employees (Carpentier et al., 2019; Kissel and B\u0026uuml;ttgen, 2015; Laradi et al., 2023; Thang and Trang, 2024). Empirical data show that social media marketing practices such as interaction, entertainment, trendiness, and informativeness have a positive influence on brand image perceptions, thus creating stronger employer associations in competitive labor market (Althuwaini, 2022; El-Menawy \u0026amp; Saleh, 2023; Lilembalemba \u0026amp; Phiri, 2024; Salhab et al., 2023; Suprawan et al., 2025; Tarabieh, 2022), Based on the signaling theory, social media marketing serves as a channel that helps to reduce information asymmetry by converting latent brand attributes into plausible digital signals that can be easily deciphered by the stakeholders. Notably, unlike previous studies that tend to conceptualize brand image as a precursor to social media engagement, this study takes a complementary and inverted approach by positing that social media marketing is a co-creative and redefining process of brand image in digitally mediated contexts. This is indicative of the dynamic and interactive quality of digital platforms, in which brand meaning is negotiated, amplified, and validated through ongoing processes of engagement and not passively conveyed, In the recruitment setting, job seekers are more likely to use the social media presence of organizations to make inferences about the quality of the employer and organizational attributes (Carpentier et al., 2019; Confetto et al., 2023; Connelly et al., 2010, 2024). Furthermore, the abundance of information presented in social media platforms increases the corporate image perceptions and employer brand ratings (Confetto et al., 2023; Kissel and Bueggen, 2015; Thang and Trang, 2024). In addition to transmission, social media platforms are algorithmically filtering and amplifying brand-related signals, making them more visible and perceived as more credible. This operation increases the cognitive accessibility and decreases ambiguity, which allows more coherent and positive brand image development, Nevertheless, the effect of social media marketing on brand image depends on the perceived authenticity, consistency, and credibility of communicated signals, which means that not all digital interactions have the same positive impact on the creation of positive images. The Iraqi banking industry, with its economic instability, digitalization, and lack of talent, is a place where strategic use of social media marketing is necessary to improve brand image, distinguish banks, and indicate stability in uncertain situations (Al-Hachami \u0026amp; Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022; Thắng \u0026amp; Trang, 2024), It is on this basis that social media marketing is re-conceptualized as a capability-based signal construction process that does not merely communicate brand attributes but in fact, affects the cognitive construction and evaluation of brand image in the digital space.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2: Brand image positively influences Social media marketing by enhancing the visibility, credibility, and cognitive accessibility of brand-related signals in digital environments.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Social Media Marketing and Organizational Attractiveness\u003c/h2\u003e \u003cp\u003eThe immediate advantages of social media marketing are the enhanced appeal of the organization due to the interactive digital signals that potential employees interpret as an indicator of employer quality, workplace culture, and career opportunities (Carpentier et al., 2017, 2019). Empirical studies indicate that the features of social media, including social presence and informativeness, have a positive impact on employer brand attractiveness and job application intentions among potential applicants (Suprawan et al., 2025; Pham and Duy, 2022; Shahid and Ayyaz, 2023). Moreover, the perception of both instrumental and symbolic employer brand attributes is reinforced by exposure to organizational social media profiles. (Carpentier et al., 2017; Kissel \u0026amp; B\u0026uuml;ttgen, 2015), Grounded in signaling theory, social media marketing helps to decrease information asymmetry in the recruitment setting by converting latent organizational characteristics into visible digital signals on platforms where job seekers are actively seeking employer-related signals (Babikova and Bucek, 2019; Carpentier et al., 2019; Connelly et al., 2010, 2024). This viewpoint disputes previous studies that have mostly considered organizational attractiveness as a passive consequence of employer branding, by highlighting its active creation via dynamically mediated digital cues and interactive engagement procedures. This is particularly applicable in digitally mediated recruitment environments, where social media pages provide information about organizational values, diversity, and engagement, resulting in positive attitudes and word-of-mouth intentions (Brouer et al., 2021; Confetto et al., 2023; T\u0026uuml;rker \u0026amp; \u0026Uuml;ng\u0026uuml;ren, 2025), Besides the flow of information, social media platforms filter, amplify, and prioritize organizational cues, which are more visible and credible. This enhances cognitive access and reduces evaluative uncertainty, enabling potential employees to make more positive and confident judgments, The effectiveness of these signals, however, depends on how authentic, interactive, and consistent they are perceived, which implies that not all social media activities produce the same impact on the attractiveness of organizations. The economic instability, digitalization, and talent scarcity of the Iraqi banking sector precondition the necessity of strategic use of social media marketing to demonstrate the stability, innovation, and employee value propositions, raising the organizational appeal and application intentions (Al-Hachami \u0026amp; Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022), Based on this, social media marketing is redefined as a capability-based signaling infrastructure that does not merely convey organizational attributes but also actively influences the perception, evaluation, and internalization of these attributes by potential employees.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3: Social media marketing positively influences organizational attractiveness by enhancing the visibility, credibility, and cognitive accessibility of employer-related signals in digital environments.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Mediating Role of Social Media Marketing\u003c/h2\u003e \u003cp\u003eThe connection between brand image and organizational attractiveness is mediated by social media marketing, which directs brand-related cues through interactive digital platforms that enhance the perceptions of organizational prestige, credibility, and quality among the stakeholders (Carpentier et al., 2019; El-Menawy and Saleh, 2023; Salhab et al., 2023; Tarabieh, Empirical data indicate that SMM enhances the connection between positive brand perceptions and employer ratings because organizations that actively use social media indicate greater attractiveness and application intentions among potential employees (Carpentier et al., 2017; Kissel \u0026amp; B\u0026uuml;ttgen, 2015; Shahid \u0026amp; Ayyaz, 2023; Suprawan et al., 2025), Grounded in signaling theory, social media marketing is a transmission system that transforms the fixed qualities of brand image into dynamic and visible digital messages, such as interactive content, user interaction, and informational richness, which stakeholders interpret as plausible indicators of organizational quality (Connelly et al., 2010, 2024). In this process, SMM does not only communicate, but also magnifies and strengthens brand signals, making them easier to translate into positive organizational judgments. This increases cognitive access and decreases evaluative uncertainty, which allows more confident stakeholder judgments. Notably, this process builds upon signaling theory by showing that signals are not simply relayed but are algorithmically boosted and socially verified in digital ecosystems, enhancing their interpretive salience, However, the success of these signals is based on their visibility, interactivity, and perceived authenticity, implying that brand image might not be enough without successful digital amplification. This mediating position is especially important in the context of recruitment, where exposure to social media content increases both symbolic and instrumental employer brand associations, making organizations more attractive (Carpentier et al., 2017; El-Menawy \u0026amp; Saleh, 2023; Kissel \u0026amp; B\u0026uuml;ttgen, 2015), Digital transformation in the Iraqi banking industry, where economic instability, digital transformation, and talent competition are the main factors, digital transformation is central to conveying and enhancing brand image messages, allowing banks to stand out and recruit high-quality applicants (Al-Hachami \u0026amp; Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022), Based on this, social media marketing is re-conceptualized not as a communication tool, but as a capability-based signal amplification process that transforms latent brand image attributes into salient, credible, and cognitively accessible organizational perceptions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH4: Social media marketing mediates the positive relationship between brand image and organizational attractiveness in the Iraqi banking sector.\u003c/b\u003e \u003c/p\u003e "},{"header":"3. Methodology","content":"\u003cp\u003eThe research design of the study is a quantitative, cross-sectional study that will rigorously investigate the relationship between brand image, social media marketing (SMM), and organizational attractiveness in the Iraqi banking industry (Al-Hachami and Alameri, 2022; Nwanebo, 2025; ONUORAH et al., 2022). The cross-sectional method is suitable in exploring theoretically based relationships between latent constructs, especially in digitally mediated settings where perceptual constructs are relatively stable over time. Although causal inferences are viewed with a grain of salt, this design is still popular in marketing and organization studies (Hair et al., 2021), The empirical setting includes the employees and managerial personnel of the Iraqi banks that are actively involved in digital financial services and social media communication. The unit of analysis is the individual respondent. The sample was recruited based on a non-probability purposive sampling method via professional networks and online platforms because of access limitations, and because of contextual relevance (Al-Hachami \u0026amp; Alameri, 2022; Nwanebo, 2025). The number of respondents (357) was sufficient to meet minimum sample size requirements of PLS-SEM and provide sufficient statistical power (Hair et al., 2021), A structured electronic questionnaire was used to gather data in a period of four months. To increase the consistency and interpretability of responses, a five-point Likert scale (1 strongly disagree, 5 strongly agree) was used. The involvement was voluntary, anonymity and confidentiality were guaranteed, and no personally identifiable data were gathered in accordance with the ethical research principles, Multi-item scales based on previous validated studies were operationalised and adapted to the digital banking context to construct all constructs (Althuwaini, 2022; Laradi et al., 2023; Thang and Trang, 2024). The measurement of brand image was conducted with four items that included organizational reputation, prestige, trustworthiness, and familiarity (Thang and Trang, 2024). Eight items were operationalised to reflect informativeness, interaction (social presence), entertainment, and trendiness to operationalise social media marketing (Carpentier et al., 2017, 2019; Kissel and Buettgen, 2015). The attractiveness of organizations was assessed with the help of sixteen items that reflected the instrumental and symbolic values, such as economic, social, development, and application value dimensions (Carpentier et al., 2017, 2019; Jayasinghe, 2018). The constructs were all conceptualised as reflective, which is in line with previous studies and theoretical conceptualisation. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows measurement details, Measurement model was evaluated based on indicator loadings, composite reliability (CR), rho A and average variance extracted (AVE). The heterotrait-monotrait (HTMT) ratio was used to assess discriminant validity, and all the values were lower than the recommended values (Hair et al., 2021). The variance inflation factor (VIF) was used to measure multicollinearity, and all the values were less than 3.3, Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyze the data with SmartPLS 4.0, which is suitable in prediction-oriented studies, mediation analysis, and multifaceted latent models. PLS-SEM is also resistant to the breach of multivariate normality, which is verified by skewness, kurtosis, and the test of Mardia (Hair et al., 2021). Bootstrapping with 5,000 resamples was used to assess statistical significance of direct and indirect effects. This methodology is consistent with the aim of the study to create a prediction-based and capability-driven explanation of organizational performance in digitally mediated settings, Procedural remedies were applied to overcome common method bias, such as assurance of anonymity and design of questionnaires. Harman single-factor test statistically revealed no dominant factor, with full collinearity VIF values less than 3.3 (Kock, 2015), The non-response bias was evaluated by comparing the early and late respondents and no significant differences were found (Groves and Peytcheva, 2008). The Gaussian copula method was used to test endogeneity, and there was no significant impact on the estimated relationships (Hult et al., 2018). Additional robustness tests were done to guarantee the stability and consistency of the results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasurement Scales and Construct Operationalization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSource(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDimensions / Sub-scales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of Items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSample Item(s)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThắng \u0026amp; Trang (2024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReputation, Prestige, Trustworthiness, Familiarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;I have heard many good things about this company.\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Marketing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarpentier et al. (2017, 2019); Kissel \u0026amp; B\u0026uuml;ttgen (2015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInformativeness, Interaction, Entertainment, Trendiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;The organization\u0026rsquo;s social media provides useful information.\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBerthon et al.; Jayasinghe (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEconomic, Social, Development, Application Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;This organization offers good career opportunities.\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Descriptive Statistics\u003c/h2\u003e \u003cp\u003eTo examine the distributional properties of the study variables, the descriptive statistics were computed at construct and dimensional levels. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, brand image, social media marketing (SMM), and organizational attractiveness have mean values that are above the scale midpoint, which suggests that there is an overall inclination towards consensus among respondents in the existence of positive organizational perceptions and digital engagement practices. The highest of the study constructs in terms of the means of social media marketing is the aggregate level, followed by organizational attractiveness and brand image, which illustrates the centrality of digital interaction in the development of stakeholder perceptions, At the dimensional level, brand image has high mean values in all its elements, especially in reputation and trustworthiness, which show high perceptions of organizational credibility among the respondents. The dimensions of social media marketing show variability with informativeness and interaction (social presence) reporting the highest mean values, which indicates that the signaling environment is characterized by information richness and interactive visibility, and the values of entertainment and trendiness are relatively moderate, In the same vein, the dimensions of organizational attractiveness show that the economic and development value dimensions have a relatively higher mean score, then social and application value, which shows the significance of both instrumental and symbolic benefits in determining organizational attractiveness. The values of standard deviation show that there is a moderate dispersion of all constructs, which implies that there is a reasonable variability in responses, Moreover, the skewness and kurtosis values are within acceptable limits (skewness of \u0026plusmn;\u0026thinsp;2 and kurtosis of \u0026plusmn;\u0026thinsp;7), which proves that there is no extreme non-normality and the data can be used to model the variance-based structural equation and test the hypothesis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBrand Image\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrestige\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrustworthiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamiliarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSocial Media Marketing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformativeness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInteraction (Social Presence)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntertainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrendiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eOrganizational Attractiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEconomic Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDevelopment Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApplication Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e: All values fall within acceptable normality thresholds.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Reliability and Validity\u003c/h2\u003e \u003cp\u003eThe measurement model was evaluated in accordance with the guidelines of PLS-SEM (Hair et al., 2021), assessing the reliability of indicators, internal consistency, convergent validity, discriminant validity, and collinearity of the reflective measurement model. Although all indicators are within the recommended thresholds, there are slight differences in outer loadings, which are within acceptable limits and do not influence construct validity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasurement Model Assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItems (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCronbach\u0026rsquo;s Alpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003erho_A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eComposite Reliability (CR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Marketing (SMM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness (OA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInternal consistency reliability and convergent validity are achieved, with the values of Cronbach alpha, rho A, and composite reliability being above the recommended value of 0.70, and the average variance extracted being above 0.50 (Hair et al., 2021). These findings affirm that the constructs have high internal consistency and reasonable convergent validity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant Validity (HTMT)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Marketing (SMM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness (OA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe heterotraitmonotrait ratio (HTMT) was used to measure discriminant validity because it is more sensitive in identifying the absence of discriminant validity. The values of all HTMT are less than the conservative value of 0.85 and the bootstrapped confidence intervals do not include 1, which proves that there is sufficient discriminant validity and conceptual distinction between constructs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOuter Loadings and Measurement VIF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem Range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoading Range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVIF Range\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI1 \u0026ndash; BI4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.76\u0026ndash;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.70\u0026ndash;2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Marketing (SMM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMM1 \u0026ndash; SMM8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u0026ndash;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.80\u0026ndash;2.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness (OA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOA1 \u0026ndash; OA16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026ndash;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.70\u0026ndash;2.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOuter loadings were used to determine indicator reliability. The indicators are loaded on their constructs (\u0026ge;\u0026thinsp;0.70), which proves sufficient indicator reliability (Hair et al., 2021).\u003c/p\u003e \u003cp\u003eThe level of multicollinearity was tested at the measurement level through variance inflation factors (VIF), and all the values were less than the conservative level of 3.3, which means that there are no collinearity issues.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFull Collinearity Assessment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull VIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Marketing (SMM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness (OA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFull collinearity VIF values were also analyzed to further evaluate the possibility of endogeneity and common method bias. All the values are less than 3.3, which further confirms that the model does not have any pathological collinearity or endogeneity issues (Kock, 2017), The measurement model shows a high level of reliability and validity in all the evaluation criteria as shown in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The internal consistency and convergent validity are well established, and all constructs are above the recommended levels, Strong outer loadings confirm indicator reliability, whereas the values of VIF at the measurement level demonstrate that the issue of multicollinearity is not a concern. The HTMT ratios below the conservative level support discriminant validity, which guarantees a clear conceptual differentiation between constructs, Moreover, the complete evaluation of collinearity proves that there are no endogeneity problems, which strengthens the validity of the measurement model. Taken together, these findings give a solid empirical evidence that the constructs are theoretically based, statistically sound and empirically different, thus giving a solid and theoretically consistent base to the further estimation of the structural model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Structural Model Assessment\u003c/h2\u003e \u003cp\u003eThe structural model was tested to test the hypothesized relationships between brand image, social media marketing (SMM), and organizational attractiveness through regression-based estimates in line with PLS-SEM interpretation logic.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStructural Model Results with Confidence Intervals\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelationship\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI \u0026rarr; OA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.31, 0.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMM \u0026rarr; BI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.54, 0.71]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSMM \u0026rarr; OA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.37, 0.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBI \u0026rarr; SMM \u0026rarr; OA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.21, 0.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe findings are very empirical in supporting all hypotheses proposed. In particular, H1, H2, and H3 are accepted, which means that brand image and social media marketing have strong positive impacts on organizational attractiveness, and social media marketing has a strong positive impact on brand image. These results affirm the inter-relationship between branding and online interaction in the development of organizational attractiveness, Regarding the magnitude of the effect, social media marketing has a significant and statistically significant influence on brand image ( 0.63), which indicates its importance as a key factor in brand perception formation in the digital space. Moreover, SMM has a significant direct effect on organizational attractiveness (=\u0026thinsp;0.48), which implies that digitally mediated relationships are essential in influencing stakeholders in their evaluations, The fact that brand image has a positive influence on organizational attractiveness ( 0.42) is also important, which confirms the notion that brand image is a basic signaling system that organizations rely on to project prestige, credibility, and value to prospective employees, Moreover, the mediation analysis (H4) indicates that there is a strong indirect impact of brand image on organizational attractiveness via social media marketing (=\u0026thinsp;0.30), which proves that SMM is a major transmission channel that transforms latent brand attributes into visible and evaluative digital cues. This observation confirms the theoretical claim that digital platforms do not simply relay but enhance and operationalize brand signals in digitally mediated spaces.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Coefficient of Determination, Predictive Relevance, Effect Size, and PLSpredict\u003c/h2\u003e \u003cp\u003eThe coefficient of determination (R 2 ), predictive relevance (Q 2 ), effect size (f 2 ), and out-of-sample predictive performance through PLSpredict were used to evaluate the explanatory power, predictive relevance, and relative importance of the structural relationships as shown in Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoefficient of Determination (R\u0026sup2;) and Predictive Relevance (Q\u0026sup2;)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndogenous Construct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrand Image (BI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganizational Attractiveness (OA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect Size (f\u0026sup2;)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelationship\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ef\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEffect Size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMM \u0026rarr; BI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLarge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI \u0026rarr; OA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSmall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMM \u0026rarr; OA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePLSpredict Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRMSE (PLS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSE (LM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePredictive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePredictive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePredictive\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe findings show that the model accounts 40 percent of the variance in brand image and 52 percent in organizational attractiveness, which is moderate explanatory power in line with the set standards. This degree of explanatory power is deemed to be strong in the context of marketing and organizational research, where the constructs of perception and behavior are complex in nature and affected by various factors (Hair et al., 2021). Moreover, all the Q2 values are greater than zero, which proves that the model has sufficient predictive relevance and can produce meaningful in-sample predictions, In addition to explanatory power, effect size analysis gives a more in-depth understanding of the relative contribution of each structural relationship. The social media marketing has a significant impact on brand image (f 2\u0026thinsp;=\u0026thinsp;0.48), which highlights its key position as one of the key factors in the formation of brand perception in the digital world. Conversely, the direct influence of brand image on organizational attractiveness is relatively low (f 2\u0026thinsp;=\u0026thinsp;0.14), which implies that brand-related perceptions might not be enough to completely influence stakeholder judgments, The social media marketing shows a moderate impact on the attractiveness of the organization (f 2\u0026thinsp;=\u0026thinsp;0.20), which indicates that it is one of the primary ways in which the digital interaction can be converted into organizational attractiveness. This implies that SMM is not just a channel of communication but a dynamic perception-making force, Notably, the results of the PLSpredict model give further indications of the predictive validity of the model. The PLS-SEM estimates are better than the linear model benchmark (LM) in all indicators, as shown by reduced RMSE values. The majority of indicators indicate lower values of RMSE than the LM benchmark, which proves that the model has a better out-of-sample predictive power, which can be applied to predictive models, not only to explanatory modeling, Taken together, these results indicate a signal amplification viewpoint, according to which the effect of brand image on organizational attractiveness is partially mediated and enhanced by social media marketing. This supports the conceptualization of SMM as a capability-based process that transforms latent brand attributes into visible, decipherable, and impactful digital cues in the context of recruitment and stakeholder assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Mediation Analysis\u003c/h2\u003e \u003cp\u003eThe mediation analysis is an extension of the structural model that demonstrates that the relationship between brand image and organizational attractiveness is mediated by social media marketing (SMM) to some extent. The indirect influence is so high that SMM is worth considering as one of the most important processes that transform the perceptions of the brand into positive organizational judgments, This observation is in line with the signaling theory that states that the usefulness of signals is not only a question of their presence but also their visibility, interpretability, and credibility. In this regard, social media marketing can be viewed as a signal amplification process that converts latent brand image attributes into visible and interactive digital signals, thus increasing their influence on the stakeholders in terms of their judgments, The findings show that brand image has a direct positive impact on organizational attractiveness, but its impact is enhanced by social media marketing. This trend indicates that social media marketing is partially mediated, i.e. it does not replace the direct impact of brand image. This implies that brand image might not be enough to influence the perceptions of the stakeholders to the full extent unless it is well communicated and reinforced using digital platforms, A deeper analysis of the indirect effect shows that the organizations that use social media marketing are better at transforming positive brand perceptions into increased organizational appeal. Conversely, when there is no robust digital interaction, the effect of brand image is relatively weakened, which means that the conversion of brand cues into evaluative results is conditional on digital amplification processes. The magnitude of the indirect effect also highlights the pivotal role of digitally mediated interactions in influencing stakeholder assessments, Notably, the mediation effect is significant, but the data is cross-sectional, which requires care in causal interpretation. Based on this, the results are to be interpreted as reflective of underlying processes and not causal relationships, In general, the findings contribute to a mechanism-based approach, which makes social media marketing a capability-based signal amplification channel where brand image is converted into organizational attractiveness in digital and high-uncertainty settings, In order to guarantee the stability and validity of the estimated relationships, and to deal with the possible issues of model misspecification, multicollinearity, and endogeneity, a set of robustness checks were performed, as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, In particular, the results of multicollinearity diagnostics show that all the values of the variance inflation factor (VIF) are lower than the conservative value of 3.3, which proves that there are no collinearity issues between the constructs of predictors. Moreover, another model specification, which reversed the direction of the key relationships (e.g., the reverse effect of organizational attractiveness on social media marketing), had less explanatory power than the proposed model, which is another empirical evidence of its superiority and theoretical consistency, In addition, bootstrapping findings indicate that the parameter estimates are consistent and the significance levels are consistent across resamples, which supports the accuracy and consistency of the results. The full collinearity test also shows that there is no indication of endogeneity problems, which implies that the estimated relationships are not likely to be systematically biased, Overall, these robustness checks are a positive sign that the model is stable, methodologically sound, and not sensitive to other specifications, which enhances the belief in the validity and generalizability of the study results.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRobustness Checks Summary\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobustness Test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKey Result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMulticollinearity (VIF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll values\u0026thinsp;\u0026lt;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndicates absence of collinearity concerns among predictor constructs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlternative Model Specification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower explanatory power\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSupports the superiority and theoretical coherence of the proposed model\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBootstrapping Stability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStable estimates with consistent significance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConfirms precision and reliability of parameter estimates across resamples\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndogeneity (Full Collinearity VIF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo issues detected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuggests absence of severe endogeneity and unbiased estimations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe robustness checks are continuously performed to make sure that the model is stable, reliable, and not sensitive to other specifications, which enhances the credibility, robustness, and generalizability of the empirical findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe results of this research offer strong empirical evidence and resolve a significant conflict between the conventional branding rationales and digitally mediated stakeholder perceptions. In particular, although brand image has traditionally been defined as a fixed and internally controlled resource, the findings show that its influence on organizational attractiveness is becoming more and more dependent on the effectiveness with which it is stimulated and enhanced by digital engagement processes. This redefines branding as a dynamic, interaction-based process, and provides a better understanding of how brand image, social media marketing (SMM), and organizational attractiveness interact, The validation of Hypothesis 1 supports the importance of brand image as a major contributor to organizational attractiveness, which is consistent with previous studies that highlight its impact on stakeholder perceptions and employer branding outcomes (Hair et al., 2018; Santiago and Tiago, 2025; Sivertzen et al., 2013; Thang and Trang, 2024). Nevertheless, in addition to affirming this relationship, the results indicate that brand image alone cannot be effective in digitally mediated settings unless it is constantly converted into visible and interactive cues, In the same vein, Hypothesis 2 emphasizes the strong influence of social media marketing on brand image, showing that digitally mediated interactions do not just convey brand attributes but actually create and co-construct them in real time (Marquez-Oyakawa et al., 2025). This means that the one-way brand communication will be changed to a more participatory and platform-based branding logic, Hypothesis 3 further confirms the pivotal role of social media marketing in enhancing organizational attractiveness, consistent with prior studies on digital marketing and employer branding (El-Menawy \u0026amp; Saleh, 2023; Sivertzen et al., 2013). More to the point, this association emphasizes the fact that attractiveness is no longer produced by organizational messaging per se, but by continuous digital interactions that signify credibility, transparency, and quality of interaction, Notably, the results support Hypothesis 4, since they establish the mediating role of social media marketing, implying that the relationship between brand image and organizational attractiveness is mediated by digitally mediated engagement. This observation demonstrates a more profound process: social media marketing is not just a channel of transmission but a process of transformation that transforms latent brand qualities into visible and evaluative cues (Bahri-Ammari et al., 2022; Kissel and Buettgen, 2015; Thang and Trang, 2024), More to the point, these results demonstrate a basic contradiction in the modern branding studies: as much as organizations invest a lot of money in creating a good brand image, the success of these investments is determined by how well they can translate the images into dynamic, digitally mediated experiences. This makes it difficult to adhere to the traditional assumptions that brand image leads to positive outcomes directly, and the value realization in the digital environment is contingent and process-based, In addition to the structural relationships, the model has a high level of explanatory power and predictive relevance, which supports its empirical validity and out-of-sample predictive ability (Hair et al., 2018, 2021; Shmueli et al., 2019). The study is methodologically rigorous, as it handles the possible endogeneity and collinearity issues with full collinearity tests (Hult et al., 2018; Kock, 2015, 2017). It is important to note that the methodological approach supports a prediction-based conception of the impact of digitally mediated capabilities on organizational outcomes, which is not within the explanatory models.\u003c/p\u003e \u003cp\u003eTheoretically, this study adds to the employer branding and signaling theory by rebranding social media marketing as a signal amplification mechanism founded on capabilities rather than a communication tool. This reframing transforms the view of digital marketing as a passive channel to an active mechanism that operationalizes and strengthens brand-related cues in digitally mediated situations. In a broader sense, it adds to the new discussions of value construction and perception in digital ecosystems, where visibility, interaction, and responsiveness are the key aspects of organizational assessment.\u003c/p\u003e \u003cp\u003eThe managerial implications of the results are that organizations are no longer to be passive in brand-building efforts but rather actively organize digital engagement strategies that continuously reaffirm and translate brand attributes into observable cues. This means that in competitive talent markets, organizational attractiveness is becoming more and more determined by the capacity of the firm to have a stable and interactive digital presence. In this way, employer branding competitive advantage is no longer based on what organizations are, but on how well they communicate and implement their identity in the digital realm, these contributions, the study has some limitations. The cross-sectional design limits causal inference, and the use of self-reported data could lead to potential bias, but procedural remedies and robustness checks were used to address these issues (Kock, 2015, 2017). It is suggested that future research must take into account longitudinal designs or multi-source data to further validate the proposed relationships and explore their time dynamics across different sectors and digitally transforming settings, By overcoming these constraints, future studies will be able to create a more causally based and strategically applicable concept of how digitally mediated engagement can convert organizational value into long-term competitive advantage.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eOverall, the current research offers strong and theoretically supported empirical data that brand image contributes to organizational attractiveness to a considerable extent, and social media marketing is an essential mediating variable. This correlation was strictly tested and validated with the help of partial least squares structural equation modeling, which proved a significant explanatory power and predictive relevance (Hair et al., 2018, 2021; Shmueli et al., 2019), The effect size analysis also highlighted the high impact of brand image on social media marketing, and the mediation findings show that the effect of brand image on organizational attractiveness is greatly enhanced by digitally mediated engagement. These results emphasize that brand image effectiveness is not achieved to its full extent in isolation but is enhanced by interactions through social media, This study contributes to theoretical knowledge by redefining social media marketing as a signal amplification mechanism based on capabilities within the signaling and employer branding theories, as opposed to conventional views. In particular, it transforms digital marketing into an active mechanism that operationalizes and reinforces brand-related cues in interactive online spaces, thus influencing the perceptions of stakeholders more effectively (Bahri-Ammari et al., 2022; Carpentier et al., 2019; Confetto et al., 2023; Kissel and Buettgen, 2015; Santiago and This view is consistent with the new studies that focus on the importance of social media in communicating employer brand qualities like competence and warmth, which increase organizational appeal and job seeker intentions (Carpentier et al., 2019; Suprawan et al., 2025) At the managerial level, organizations are encouraged to combine strategic social media activities to enhance brand signals, especially in competitive talent markets where interactive digital presence is paramount (Carpentier et al., 2019; El-Menawy and Saleh, 2023; Marquez-Oyakawa et al., 2025). This involves creating content that is more socially present and informative, capitalizing on user-generated content, and promoting real-time engagement to build employer brand equity and attract high-quality talent, especially digitally oriented generations like Generation Z (El-Menawy and Saleh, 2023; Santiago and Tiago, 2025; Suprawan et al., 2025; Laradi et al., 20 This management implication supports the main conflict between fixed brand perceptions and moving digital amplification processes, In spite of these contributions, the study has some limitations. The cross-sectional nature limits causal inference, and the use of self-reported data can introduce residual bias, but robustness checks of endogeneity, collinearity, and common method bias were performed (Hult et al., 2018; Kock, 2015, 2017; Silva and Dias, 2022). It is recommended that future studies consider longitudinal and multi-source designs to study the temporal dynamics across sectors and digitally changing contexts, possibly with experimental designs and a variety of generational cohorts to increase generalizability (Hanu et al., 2021; Jasim et al., 2026; Stadler et al., 2025; Thang and Trang, 2024), Finally, this paper shows that in digitally mediated settings, the attractiveness of organizations is no longer defined by what companies say, but by how well they modify and enhance brand messages by means of interactive digital interaction.\u003c/p\u003e\n\u003ch3\u003e6. Managerial Implications\u003c/h3\u003e\n\u003cp\u003eThis research has important strategic implications to banking executives in an ever-digitized and talent-competitive world. First, the findings indicate that brand image is no longer enough to make organizations more attractive unless it is actively converted into visible and credible cues. This means that managers must no longer be content with the old-fashioned reputation-building activities but rather plan to have integrated communication capabilities that constantly project organizational values, credibility, and employer quality via platform-based communication. Second, social media marketing is not only a promotional tool but a strategic capability that allows banks to enhance brand-related cues and proactively influence stakeholder perceptions in real time. Based on this, managers are advised to use interactive, data-driven, and authentic social media functions to promote career opportunities, organizational culture, employee value propositions, and institutional stability in a way that engagement is meaningful and strategically aligned with employer branding goals. Third, the mediating effect of social media marketing suggests that the attractiveness of organizations is enhanced when positive brand perceptions are successfully converted into visible online experiences. This demands greater cross-functional coordination and integration of marketing, human resource management, and corporate communication functions, which will allow the transmission of signals across all touchpoints in a consistent and coherent manner. Lastly, in unstable and information-scarce settings like the Iraqi banking industry, managers ought to understand that potential employees are becoming more and more critical of organizations in terms of visible indicators, as opposed to reputational assertions. The inability to have an active, credible, and responsive online presence can seriously undermine the attractiveness of the employer and destroy competitive positioning. Thus, technology-based engagement cannot be regarded as a marginal activity, but rather as a fundamental strategic competence that defines the capacity of the bank to compete in the labor market and remain competitive in the labor market in the face of changes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eH.M.T. conceptualized the study, conducted data collection, and wrote the main manuscript text. H.M.T. and S.A.S.A. designed the methodology and performed the statistical analysis. S.A.S.A. contributed to the literature review and critically revised the manuscript. H.M.T. prepared the figures and tables. All authors reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbunaila, A. S. H., \u0026amp; Kadhim, S. M. (2022). 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Digital Disruption in Banking. \u003cem\u003eAnnual Review of Financial Economics\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1), 243. \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ehttps://doi.org/10.1146/annurev-financial-100719-120854\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"sn-business-and-economics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"43546","submissionUrl":"https://submission.nature.com/new-submission/43546/3","title":"SN Business \u0026 Economics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Brand Image, Social Media Marketing, Organizational Attractiveness, Digital Engagement, Signaling Theory, Employer Branding, Partial Least Squares Structural Equation Modeling, Emerging Markets","lastPublishedDoi":"10.21203/rs.3.rs-9612378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9612378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study will examine the connection between brand image and organizational attractiveness by examining the mediating role of social media marketing (SMM) in the Iraqi banking sector, The paper, based on the signaling theory, re-conceptualizes SMM as a capability-based signal amplification process that converts latent brand characteristics into visible signals, thus alleviating information asymmetry ,The study design was a quantitative, cross-sectional research, in which 357 employees personnel were surveyed and the data were examined with the help of partial least squares structural equation modeling (PLS-SEM). The results confirm that brand image and SMM have a significant positive impact on organizational attractiveness, and the mediation analysis shows that SMM partially mediates and strengthens this relationship. The model has a moderate explanatory power and high predictive relevance, and PLSpredict proves better out-of-sample predictive performance, Theoretically, this study makes three key contributions. First, it redefines social media marketing as an active, capability-based signaling infrastructure, as opposed to a passive communication channel. Second, it provides a mechanism-based explanation of how brand image is operationalized into organizational attractiveness in the form of observable and interactive engagement processes. Third, it extends the existing body of research on signaling and employer branding by demonstrating how signals are amplified in dynamic and interactive situations, Managerially, the results point to the fact that organizations should not be content with the traditional brand-building, but they need to strategically plan interactive social media potentials to make organizations more attractive in competitive labor markets. This brings out an important contradiction between predetermined brand perceptions and dynamic signal amplification mechanisms.\u003c/p\u003e\n\u003cp\u003eJEL Classification: M31, G21, M12, M37\u003c/p\u003e","manuscriptTitle":"The Effect of Brand Image on Organizational Attractiveness: The Mediating Role of Social Media Marketing in the Banking Sector","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 13:27:12","doi":"10.21203/rs.3.rs-9612378/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-06T07:54:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T04:42:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-06T04:42:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"SN Business \u0026 Economics","date":"2026-05-04T22:34:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"sn-business-and-economics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"43546","submissionUrl":"https://submission.nature.com/new-submission/43546/3","title":"SN Business \u0026 Economics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e83ef59d-4122-44af-9fe5-95530d4ac5a8","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"17","date":"2026-05-06T07:54:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-06T04:42:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-06T04:42:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"SN Business \u0026 Economics","date":"2026-05-04T22:34:08+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T13:27:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 13:27:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9612378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9612378","identity":"rs-9612378","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}