The Impact of Followers’ Social Identity on Fashion Purchase Intention: The Mediating Role of Source Credibility

Abstract

This study examines how followers’ social identity dimensions—cognitive, evaluative, and affective—affect their purchase intention for fashion products promoted by Instagram influencers. It also explores the mediating role of source credibility factors, including trustworthiness, expertise, and attractiveness, in strengthening this relationship. Targeting millennial females, a key fashion consumer group, the study applies social identity theory, source credibility theory, and influencer marketing literature to develop its conceptual framework. A quantitative, correlational approach was used, employing a self-administered questionnaire distributed via a convenience snowball sample of millennial females in Erbil, Kurdistan. Data from 421 respondents collected between were analyzed using SPSS AMOS version 24. Findings reveal that all social identity dimensions significantly influence purchase intention, and source credibility factors play a direct mediating role in this relationship. These insights offer practical implications for marketers and influencers, helping them understand the impact of followers’ social identity on purchasing behavior and refining influencer marketing strategies. This research expands influencer marketing literature by demonstrating the mediating effect of source credibility on the link between social identity and purchase intention. This research provides practical implications for enhancing millennial consumers’ purchase intentions by leveraging social identity mechanisms. The findings offer valuable insights for both social media influencers and brands seeking to employ influencer marketing strategies effectively in fashion promotion.

1. Introduction

The digital revolution has reshaped how people interact, with social media becoming an integral part of daily life [1]. As of January 2024, global internet users reached 5.35 billion, with 5.04 billion active users on social media [2]. Millennials, born between 1980 and 2000, constitute over 80% of social media users and are digital natives who rely heavily on technology [3,4]. Platforms such as Instagram, Facebook, TikTok, YouTube, and Twitter provide a virtual space for engagement, communication, and content sharing [5,6].

The rise of social media has driven new marketing strategies [7], particularly influencer marketing, which leverages the popularity of influencers to promote brands [8,9]. Influencers, including bloggers, celebrities, and digital entrepreneurs, serve as trusted figures, shaping followers’ opinions and purchase decisions [10,11]. Businesses increasingly collaborate with social media influencers, as research shows that influencer marketing is significantly more effective than traditional advertising [12] as consumers perceive influencers as fellow users rather than traditional advertisers, which enhances credibility and trust [13]. Currently, over 75% of companies utilize influencer marketing, and global spending in this area is projected to reach $373 million by 2027 [14,15].

Among social media platforms, Instagram stands out as the preferred choice for influencer marketing due to its high engagement rates [16]. With 1.21 billion active users in 2021, Instagram is projected to reach 1.44 billion by 2025 [17]. Nielsen Research highlights millennials’ preference for Instagram, particularly for shopping purposes [18]. Notably, the largest demographic of Instagram users falls within the 25–34 age group (46.81%), followed by the 18–24 group (33.17%) [19]. Female users dominate Instagram usage across these age groups, making them a key audience for influencer marketing [20].

The rapid rise of influencer marketing has led researchers to examine its impact on consumer behavior, particularly the factors influencing followers’ purchase intentions [21,22]. Social identity theory is a key framework in understanding how individuals associate with specific groups, shaping their behaviors and decisions [23]. People construct social identities through categorization and comparison, seeking validation within social groups [24]. In digital communities, influencers play a crucial role in shaping these identities, with followers showing a preference for content that aligns with their group identity [25]. Online engagement fosters a sense of belonging, influencing followers’ interactions with influencer marketing [26]. Prior research highlights the significance of digital community relationships in shaping consumer decisions, particularly when influencers provide recommendations [25]. Given the importance of social identity in digital interactions, understanding its role in influencer marketing is critical.

Influencers’ credibility is another significant factor affecting consumer behavior. According to [27], influencers exert more influence over their followers than traditional advertisements. Credibility encompasses trustworthiness, expertise, and attractiveness, key elements in predicting consumer responses to influencer marketing [28]. The source credibility model posits that influencers’ perceived reliability enhances the effectiveness of their recommendations [29]. Studies show that influencer credibility is a major predictor of purchase intentions, as consumers rely on credible sources for information [30,31]. Trustworthiness and expertise significantly impact consumer attitudes toward brands [9,32,33]). Weismueller et al. (2020) further confirm that social media influencers’ credibility strongly influences followers’ purchasing behavior [34].

The fashion industry has embraced social media and influencer marketing, recognizing its power to shape consumer preferences [10,35,36]. As fashion trends gain prominence, consumers become more selective, increasingly relying on influencers for guidance [37]. Fashion brands leverage influencers to showcase designs, promote styles, and drive consumer engagement [38]. Globally, the fashion industry is a significant economic force. If compared to national economies, it would rank as the seventh-largest in GDP terms [39]. The sector was valued at approximately $2.5 trillion before the COVID-19 pandemic. However, the pandemic caused an 18.1% decline in the global apparel market in 2020 [40]. Recovery efforts led to a 21% revenue increase in 2021, with continued growth into 2022 [41]. The industry employs 430 million people globally, reinforcing its economic significance [42]. Fashion consumption has surged in recent decades, driven by the rise of fast fashion, which emphasizes affordability and short product life cycles [43]. The global consumption of fashion products stands at 62 million tonnes annually, projected to reach 102 million tonnes by 2030 [44]. Social media plays a pivotal role in influencing fashion trends, with Instagram emerging as the dominant platform for fashion-related content [45].

The last decade has seen influencer marketing move from a tactical add-on to a strategic channel that shapes late-stage consumer decisions and symbolic consumption. Social platforms (especially Instagram) combine high visual affordances with social feedback mechanisms, which let influencers not only communicate product features but also model lifestyles, norms and identity repertoires that followers can adopt. In fashion—a primarily hedonic and identity-expressive product category—these identity signals matter more than in many utilitarian sectors because clothing choices are tightly bound to self-presentation and group membership (see literature on fashion and social identity). As recent empirical reviews and field studies show, influencers affect discovery, evaluation and ultimately purchase choices, while brands are increasingly relying on influencer partnerships to activate symbolic meaning and social proof. Fashion brands are increasingly integrating influencer marketing into their digital strategies. Influencers engage consumers through Instagram stories, contests, and brand collaborations, making marketing more interactive and engaging [46]. Social media influencers significantly impact followers’ opinions, shaping their style choices and purchase decisions, as a result, brands actively collaborate with influencers to enhance their market presence and brand image [47]. Theoretically, this paper integrates two complementary bodies of work. Social Identity Theory (SIT) explains how people define themselves through group membership and how identification motivates conformity to group norms and preferences; in digital communities, influencers can become focal ingroup exemplars whose tastes and endorsements serve as normative signals. The source credibility model (trustworthiness, expertise and attractiveness) explains variation in how persuasive those signals are once received. Framing both together produces a clear causal chain: (a) followers’ social identity (cognitive, evaluative, affective elements) increases attention and receptivity toward influencer cues; (b) that social identification shapes perceptions of the influencer’s credibility; and (c) perceived credibility translates identification into higher purchase intention. This integrated route clarifies how identification matters in influencer marketing (not merely that it matters).

Fashion consumption is among the most identity-laden forms of buying: clothing choices are used to signal membership, status and group norms, and thereby to construct or communicate the self. While prior influencer research has established that message attributes and influencer attributes correlate with follower responses, these studies often stop short of specifying the social-psychological mechanism that converts exposure into purchase. Social identity offers that mechanism: cognitive identification explains category-based recognition (I belong/I am like this group), evaluative identification captures the self-esteem gains from group membership (prestige and desirability), and affective identification covers emotional attachment and belonging. Disaggregating social identity into these three components therefore permits a finer-grained test of which identity processes drive fashion purchase intention and how they do so through perceived influencer credibility. This is particularly important for fashion, where symbolic congruence and affective ties frequently trump instrumental product information. In addition, fashion consumption patterns are strongly shaped by both generational cohort and gender, with prior research consistently demonstrating clear differences across generations and between males and females [48,49]. These variations underscore the importance of developing a deeper understanding of fashion consumption behaviors across different cultural contexts and geographic regions.

Prior research highlights the influence of fashion influencers on consumer purchasing behavior [10,50]. However, despite their acknowledged impact, gaps remain in understanding the mechanisms driving consumer decisions. Previous studies have focused on followers’ perceptions of influencers, message characteristics, and personal traits such as self-esteem and loneliness [26,51]. Additionally, research has explored influencer credibility, message uniqueness, and digital group dynamics in shaping consumer responses [52,53]. Despite these insights, a significant research gap remains regarding the role of social identity in influencer marketing. While previous studies examine general influencer-follower dynamics, little research investigates how social identity influences purchase intentions in the fashion industry. Furthermore, the mediating role of influencer credibility in this process remains underexplored. Accordingly, this study is attempting to answer the following two research questions: (1) what is the impact of impact of social identity on purchasing intention of fashion product among millennial females, (2) What is the mediating role of source credibility in the relationship between social identity and purchasing intention of fashion product among millennial females.

The paper is divided into five main sections. It first establishes the theoretical foundation of the research model through the literature review, followed by the research methodology. The subsequent section presents the statistical analysis and results, and the final section discusses the findings and provides the concluding remarks.

2. Literature Review

2.1. Purchasing Intention

Purchasing intention reflects a consumer’s willingness to buy a product [54]. Rooted in consumer psychology, it signifies the potential for purchasing behavior [55,56]. The Theory of Planned Behavior (TPB) [57] explains that behavioral intention is influenced by subjective norms, attitudes, and perceived behavioral control [58]. A stronger behavioral intention suggests a higher likelihood of actual behavior [59,60].

Kotler et al. (2019) describe the buying process as problem recognition, information search, alternative evaluation, purchase decision, and post-purchase behavior [61]. Understanding this process allows marketers to influence consumer decisions effectively. In the digital age, social media marketing plays a significant role in shaping purchasing intentions, particularly through social identity theory (SIT) [62]. Consumers are drawn to brands that align with their social identity, which consists of cognitive, evaluative, and affective components [63,64]. Additionally, electronic word-of-mouth (eWOM) has become crucial in shaping consumer decisions, with online recommendations influencing purchases significantly more than traditional word-of-mouth [61,65]. Another factor is parasocial interaction, where followers perceive a personal connection with influencers, making them more likely to trust and act on their recommendations [51,66]. Source credibility, including trustworthiness, expertise, and attractiveness, further enhances influencers’ impact on consumer behavior [67,68,69].

2.2. Millennial Females

Research consistently showing that certain age groups and women tend to engage more actively in fashion purchasing. Women exhibit higher engagement in fashion-related purchases than men, with spending three times higher [70]. Studies demonstrate that Generation Y (Millennials) exhibit higher purchase frequency, stronger fashion fanship, and greater fashion expenditure compared to older cohorts, and within these groups females show significantly higher yearly expenditure on fashion purchases compared to males, reflecting distinct consumption behaviors shaped by socialization, fashion consciousness, and in some cases, impulsive buying tendencies [48,49]. Female consumers place greater emphasis on trust in purchasing decisions [71,72]. Millennials, defined as individuals born in the last two decades of the 20th century, represent a dominant consumer group [73,74]. They are highly active in online shopping, social media interactions, and digital brand engagement [75,76]. Millennials are particularly brand-conscious yet prioritize price and features over brand names [77,78]. They also allocate significant resources to fashion and clothing for self-expression [79].

2.3. Social Identity

Tajfel and Turner (1979) introduced Social Identity Theory (SIT) [80], which posits that individuals define themselves based on group membership [81]. Social identity influences attitudes, beliefs, and behaviors, including purchasing decisions [26,82]. Customer-brand identification strengthens consumer relationships with brands, fostering loyalty and trust [83,84]. The theory also explains consumers’ attachment to influencers, as followers seek identity similarity, identity distinctiveness, and identity prestige with influencers [85]. Thus, the following hypothesis is formulated:

H1. 

Social identity has a significant positive effect on purchase intention.

2.3.1. Cognitive Social Identity

Cognitive social identity refers to self-categorization, where individuals recognize their group membership and distinguish in-groups from out-groups [23,86]. According to the Social Categorization Theory [87], individuals form psychological identities through categorization based on past experiences, expectations, and motivations [88]. Therefore, this study extends prior work by arguing that cognitive categorization on Instagram can act as a cognitive shortcut in decision-making, reinforcing alignment with influencer-endorsed brands. Accordingly, the following hypothesis is formulated:

H1.1. 

Cognitive social identity positively influences purchase intention.

2.3.2. Evaluative Social Identity

Evaluative social identity relates to self-esteem derived from group membership [89]. Group prestige fosters positive self-worth [90]. Social Comparison Theory [91] suggests individuals engage in upward comparisons (aspiring to superior groups) and downward comparisons (differentiating from lower-status groups) to reinforce identity [23,92]. Prior studies discussed above highlight that evaluative identity often translates into positive consumer-brand associations; nevertheless, questions remain on whether group-derived self-esteem translates into transactional behaviors. By applying social comparison theory within influencer contexts, the following hypothesis is formulated:

H1.2. 

Evaluative social identity positively influences purchase intention.

2.3.3. Affective Social Identity

Affective social identity refers to emotional attachment and group belongingness [93,94]. Self-Categorization Theory suggests that people conform to in-group norms while avoiding out-group norms [95]. Emotional attachment has been shown to strengthen loyalty in both offline and digital communities [83]. Yet, affective identity may be contingent on the authenticity and consistency of influencer-follower interactions [26]. This alignment may reinforces purchasing decisions that align with group identity. Accordingly, the following hypothesis is formulated:

H1.3. 

Affective social identity positively influences purchase intention.

2.3.4. Millennials’ Social Identity

Millennials express their identity through social media and online interactions [96,97]. They are influenced by peer assimilation and uniqueness-seeking, shaping their brand preferences and purchasing behavior [98,99,100]. Millennials dedicate time and money to fashion as a form of self-expression [79]. Social media plays a crucial role in their shopping decisions, influencing product discovery and brand selection [101,102]. Their purchasing power continues to rise, making them a lucrative target for brands [103,104].

2.4. Influencer Marketing

The rise of influencer marketing is attributed to the growing interaction between influencers and their followers [26,105]. Businesses collaborate with influencers to enhance brand awareness and purchasing intention [106]. Influencers receive compensation through payments, free products, or experiences [107]. A social media influencer is a content creator with expertise in a niche area, generating a dedicated following [108]. Unlike celebrities, influencers build their reputation solely through online presence and engagement [109,110]. Research indicates that followers trust influencers more than traditional celebrities, making influencers endorsements more effective [68,111,112]. Furthermore, ensuring a brand-influencer fit is critical for successful marketing campaigns [113]. Prior studies focus on either the influencer-brand match [114,115] or influencer-consumer fit [46]. However, the triadic fit—influencer, brand, and consumer—requires more research [116].

Influencer effectiveness depends on three key areas:

• Follower-influencer relationships: Authentic engagement fosters trust and loyalty [117].
• Influencer characteristics: Expertise, attractiveness, and trustworthiness enhance credibility [21].
• Content quality: Relatable, high-quality content increases consumer engagement [118,119].

Previous research highlights that an influencer’s follower size, trustworthiness, expertise, and attractiveness significantly impact follower behavior and intentions. Leung et al. (2022) found that follower size enhances engagement and influence [21]. However, Wies et al. (2020) suggest that a large following may reduce engagement, as it weakens the personal connection with followers [120]. Koay et al. (2022) demonstrated that an influencer’s expertise and trustworthiness positively affect purchase intention [16]. They also noted that attractiveness influences purchasing decisions, especially among highly materialistic individuals. Moreover, the strength of the influencer-follower relationship is crucial. Conde and Casais (2023) emphasized the role of parasocial interactions, where strong relationships allow smaller influencers to compete with larger ones in persuasive power [121]. Farivar and Wang (2022) explored the role of social identity, demonstrating that followers with a strong sense of belonging to an influencer’s community show higher purchase intentions [26].

Instagram as a Platform

Instagram, launched in 2010 and acquired by Meta in 2012, has over two billion active users as of January 2023 [17]. It serves as a key platform for influencers, especially in the fashion industry, due to its visual-centric nature [20]. Instagram’s features, such as reels, live videos, and stories, enhance engagement [46]. It also facilitates direct shopping through tagged images, encouraging impulse purchases [122]. Influencers on Instagram curate content aligned with their expertise while sharing personal aspects through stories, fostering familiarity with followers [123]. Beyond product promotion, they integrate brand messaging with their personal narratives, strengthening audience connection [116].

2.5. Source Credibility

Credibility is a key determinant of influencer effectiveness. Source credibility refers to the audience’s perception of an influencer’s reliability, authenticity, and trustworthiness [124]. This study adopts the source credibility model, which evaluates influencer impact through trustworthiness, expertise, and attractiveness [125,126]. While the source credibility model is well-established, scholars argue that its dimensions may not operate uniformly across digital contexts and different sectors. Highlighting the need for further examination, this study investigates the possible mediating impact of source credibility and its dimensions in the context of fashion among female millennials. Accordingly, the following hypothesis is formulated:

H2. 

Source credibility mediates the relationship between social identity and purchase intention.

2.5.1. Trustworthiness

Trustworthiness plays a significant role in shaping consumer behavior [127]. Influencers perceived as reliable and honest are more likely to influence purchasing decisions [16]. Those who share personal stories and interact with their audience foster emotional connections, reinforcing trust [106]. A trustworthy influencer also enhances brand credibility, leading to greater engagement and purchase intention [22,128]. Brands associated with influencers recognized as trustworthy enhanced increased level of brand attitude and brand credibility, leading to higher purchase intention [128]. Accordingly, this study suggests that the perceived trustworthiness of social media influencers could mediate the relationship between followers’ social identity and their purchasing intention towards influencer recommendations. Consequently, the following hypothesis is posited:

H2.1. 

Influencer trustworthiness mediates the relationship between social identity and purchase intention.

2.5.2. Expertise

Expertise refers to an influencer’s perceived knowledge and competence in their field [129]. Consumers are more inclined to trust and purchase products endorsed by knowledgeable influencers [34]. Wang and Scheinbaum (2018) found that expertise directly impacts consumer trust and purchase decisions [128]. Additionally, Lou and Kim (2019) noted that expertise strengthens parasocial relationships between influencers and followers [69]. When a knowledgeable individual promotes a brand, it conveys integration with follower’s aspiration, encouraging them to incorporate the brand into their self-concept [130]. Therefore, this study contends that the expertise possessed by social media influencers could mediate the relationship between followers’ social identity and their purchasing intention toward influencer’s recommendations. Thus, the following hypothesis is formulated:

H2.2. 

Influencer’s expertise significantly mediates the relationship between social identity and followers’ purchasing intention in the fashion industry.

2.5.3. Attractiveness

Attractiveness influences an influencer’s persuasiveness, as followers often associate physical appeal with credibility [129]. Studies suggest that physically attractive influencers are more effective in shaping purchasing behavior [127]. Advertisers frequently select attractive influencers, assuming they have a stronger impact on consumer perception [128]. This selection is made based on the belief that those influencers have stronger impact in shaping consumer’s behavior towards the endorsed brands.

Therefore, this study argue that the appeal of social media influencers could mediate the relationship between followers’ social identity and their purchasing intention toward influencer’s recommendations. Thus, the following hypothesis is formulated:

H2.3. 

Influencer’s attractiveness significantly mediates the relationship between social identity and followers’ purchasing intention in the fashion industry.

2.6. Conceptual Framework

The presented conceptual model, illustrated in Figure 1, combines insights from social identity theory [80], source credibility theory [131]; Ohanian (1990) and the theory of planned behavior [57,126]. The main objective is to explain the complicated dynamics impacting the relationship between followers’ social identity and their purchasing intention. The model also investigates the mediator role of source credibility in this relationship within the realm of fashion industry, with a particular focus on female millennials.

Within the scope of social identity processes, the framework investigates the cognitive dimension, where followers classify themselves within the influencer community, enhancing self-awareness and identifying shared features with in-group members [23,88,132]. The evaluative aspect describes how assessments made within this particular community influence follower’s self-esteem and group self-esteem, creating favorable group distinctiveness [89,90,133], whereas affective social identity examines the emotional commitment and positive feelings that followers experience within the influencer group, inspired by the feeling of attachment and belonging [62,93,95,134].

In terms of source credibility dimensions, the framework includes perceived trustworthiness, refers to followers’ viewpoint of influencers’ reliability and trustworthy [16,106,135]. Perceived expertise describes followers’ perceptions on influencer’s proficiency and knowledge [34,69,129], while perceived attractiveness represents followers’ perspectives on the influencers’ physical attractiveness and beauty [129,136,137].

Finally, the framework concludes with purchasing intention, capturing the potential that female millennials, impacted by their social identity and their perception of source credibility, are more likely to purchase fashion products promoted by social media influencers [59,138,139].

3. Research Methodology

This study adopts a quantitative research approach to examine the relationship between followers’ social identity, source credibility, and purchasing intention in the context of fashion influencers on Instagram. The research employs a survey-based method to collect primary data from female millennials, a key demographic in social media-driven fashion consumption.

3.1. Research Design

The study utilizes a cross-sectional survey design, which enables the collection of data at a single point in time to analyze the associations between key variables. The conceptual model is grounded in social identity theory, source credibility theory, and the theory of planned behavior, providing a theoretical foundation for hypothesis testing.

3.2. Sampling and Data Collection

The target population consists of female millennials who actively follow fashion influencers on Instagram in the Kurdistan Region of Iraq estimated at hundreds of thou-sands, as there are no official records available on the exact number. Because of Due to absence of such records probability sampling techniques can’t be used, therefore, the re-searchers utilized a non-probability, connivance sampling technique. Purposive sample was found to be consistent with the research orientation. Data was collected through an online survey distributed via social media platforms and relevant online comminutes to the female followers of fashion influencers on Instagram based in their location.to ensure that all respondents meet the inclusion criteria: (1) being female, (2) aged between 18 and 40 years, and (3) following at least one fashion influencer on Instagram.

Since the exact number of the population of this research is unknown, aiming at 95% confidence level and a 5% margin of error, the minimum recommended size of the sample of the largest possible population is 385 [140]. This sample size also covers the requirements to use structural equation modeling (SEM) with a minimum of 200 responses required for robust statistical analysis. To enhance response validity, screening questions are included to confirm participants’ eligibility before proceeding with the survey.

3.3. Survey Instrument

The survey consists of structured, close-ended questions measuring key variables using validated scales adapted from prior studies. A five-point Likert scale (1 = strongly disagree to 5 = strongly agree) is used for all measurement items.

• Social Identity: Measured using items adapted from [23,132], assessing cognitive, evaluative, and affective dimensions.
• Source Credibility: Measured through trustworthiness, expertise, and attractiveness dimensions, using items from [16,106,129].
• Purchasing Intention: Assessed using items from [59,138], evaluating the likelihood of purchasing fashion products endorsed by influencers.

Appendix A present the final questionnaire.

3.4. Data Analysis

The collected data is analyzed using SPSS and AMOS software version 29. Descriptive statistics summarize demographic characteristics, while reliability and validity are assessed through Cronbach’s alpha and confirmatory factor analysis (CFA). Structural equation modeling (SEM) is employed to test hypothesized relationships and the mediating role of source credibility in the link between social identity and purchasing intention.

3.5. Ethical Considerations

The study adheres to ethical research guidelines, ensuring informed consent, confidentiality, and voluntary participation. Respondents are informed about the purpose of the research, and their data is anonymized to protect privacy.

By employing a rigorous methodological approach, this study aims to provide empirical insights into how social identity and source credibility influence female millennials’ purchasing decisions in the fashion industry.

3.6. Sample Characteristics

The comprehensive analysis of demographic characteristics and behavioral patterns among Instagram users, with a focus on gender, age, influencer following, daily time spent on the platform, educational level, marital status, residence, monthly personal income, and occupational status, is presented in

Table 1. Sample characteristics.

Variable	Category	Count	Percent
Age	<18	10	2.4%
	18–24	79	18.8%
	24–30	157	37.3%
	30–37	143	34.0%
	37–43	26	6.2%
	>43	6	1.4%
	Total	421	100
Daily time spent on Instagram	<1	25	5.9%
	1–2	70	16.6%
	2–4	209	49.6%
	4–6	104	24.7%
	>6	13	3.1%
	Total	421	100
Education Level	less or school High	37	8.8%
	Two years diploma	80	19.0%
	Bachelor’s degree	281	66.7%
	Postgraduate	23	5.5%
	Total	421	100
Marital status	Single	180	42.8%
	Engaged	57	13.5%
	Married	178	42.3%
	Other	6	1.4%
	Total	421	100
Monthly Income	<500 $	186	44.2%
	500–1000 $	142	33.7%
	1001–2000 $	68	16.2%
	2001–3000 $	21	5.0%
	>4000 $	4	1.0%
	Total	421	100
Occupation (Current Employment Status)	employed Salary	198	47.0%
	Not employed	171	40.6%
	Run my Owen business	19	4.5%
	Others	33	7.8%
	Total	421	100

. The survey data, collected from a diverse sample, provide valuable insights into the Instagram user landscape, contributing to a better understanding of user preferences and engagement patterns.

Table 1 above shows that age distribution showcases a diverse user base, with the largest segment (37.3%) falling within the 24–30 age range. Users aged 18–24 (18.8%) and 30–37 (34.0%) also constituted significant portions, indicating a broad representation across various age groups. Daily usage patterns revealed that a considerable proportion (49.6%) spent 2–4 h on Instagram. Educational attainment varied, with 66.7% holding a Bachelor’s degree, signifying a relatively high level of education among respondents. Marital status indicated a relatively balanced distribution, with single (42.8%) and married (42.3%) respondents forming the majority. In terms of income, a significant proportion (44.2%) reported a monthly income of <$500. Employed individuals with a salary constituted a major occupational segment (47.0%), while those not employed accounted for 40.6%.

4. Analysis

4.1. Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis (CFA) is utilized to validate the factor structure of the observed variables, including examining the factor loadings.

Table 2. Confirmatory factor analysis results (Factor loading).

Latent Variable	Indicator	FL	FLS	Cronbach’s α	AVE (>0.50)	CR (>0.70)
	Cognitive social identity	0.874	0.765	0.924	0.754	0.902
	Evaluative social identity	0.854	0.730
	Affective social identity	0.877	0.769
Source credibility	Attractiveness	0.816	0.666	0.909	0.717	0.884
	Expertise	0.853	0.728
	Trustworthiness	0.869	0.756
Purchase intention	Interested	0.839	0.704	0.870	0.702	0.894
	Plan	0.832	0.692
	Purchase	0.843	0.710

below outlines the evaluation of composite reliability (CR), convergent validity, and discriminant validity. Table 2 below illustrates the outcomes of discriminant validity assessment using HTMT Analysis. Factor Loading (FL), Factor Loading Squared (FLS), Cronbach’s Alpha (Cronbach’s α), Average Variance Extracted (AVE), and Composite Reliability (CR) are abbreviated as FL, FLS, AVE, and CR, respectively, in the table for convenience and clarity.

The Confirmatory Factor Analysis (CFA) outcomes, meticulously presented in Table 2, unequivocally establish the reliability and validity of the measurement model for the latent variables—Social Identity, Source Credibility, and Purchase Intention.

Table 2 indicates The Cronbach’s alpha coefficients for all variables ranged from 0.870 to 0.924, surpassing the recommended threshold of 0.70. This indicates high internal consistency among the items within each latent variable. The loadings of all items range from 0.816 to 0.877, meeting the recommended threshold of 0.50 or higher, preferably 0.70 or higher, thus validating the results [141].

Convergent validity is determined within factor loadings through composite reliability (CR) and average variance extracted (AVE). The findings indicate that composite reliability values, falling between 0.884 and 0.902, surpassing the threshold of 0.70, demonstrate commendable internal consistency. The outcomes further reveal that the average variance extracted (AVE) values varied between 0.702 and 0.754, surpassing the 0.50 threshold, which validates the utilization of the construct. As a result, all latent variables have satisfied the criteria for confirming convergent validity [142].

In summary, the CFA results foster unwavering confidence in the measurement model, affirming that the selected indicators adeptly capture the latent constructs of Social Identity, Source Credibility, and Purchase Intention in a valid and reliable manner [142].

The findings displayed in

Table 3. HTMT Analysis.

	Social Identity	Source Credibility	Purchasing Intention
Social Identity	--
Source Credibility	0.809	--
Purchasing Intention	0.785	0.792	--

reveal that all HTMT values remain under 0.85, suggesting no issues with discriminant validity. As per Henseler et al. (2015) HTMT values lower than 0.90 indicate discriminant validity among reflective variables [143]. The results additionally validate the lack of collinearity problems among latent variables (multicollinearity) and the absence of item overlap in respondents’ perceptions within the relevant variables.

Drawing from the analyses presented in Table 2 and Table 3, the following sections introduce the final version of the Confirmatory Factor Analysis (CFA) model that has been refined and adjusted based on statistical analyses and theoretical considerations, elaborated upon extensively in

Table 4. Goodness-of-fit statistics for the three-factor CFA model.

Model Tested	X2	SRMR	CFI	TLI	NFI	RMSEA
Model performance	193.93	0.028	0.991	0.987	0.983	0.051
Criterion for goodness of fit	-	≤0.08	≥0.90	≥0.90	≥0.90	≤0.10

and visually depicted in Figure 2 below.

Goodness of Fit

Various indicators are used to assess the model’s goodness of fit, encompassing the Chi-square statistic (X²), Standardized Root Mean Squared Residual (SRMR), Comparative Fit Index (CFI), Normed Fit Index (NFI), Tucker and Lewis’s Index of Fit (TLI), and Root Mean Square Error of Approximation (RMSEA).

Table 4 illustrates the Chi-square statistic value (X²) for assessing model performance is 193.93. While X² is commonly used, its sensitivity to sample size means that a significant p-value may indicate a lack of fit [144]. Therefore, researchers often supplement it with additional fit indices for a comprehensive assessment. The SRMR (Standardized Root Mean Squared Residual) gauges the standardized discrepancy, on average, amid observed and predicted correlations. Here, the SRMR value is 0.028, comfortably below the recommended threshold of 0.08 [145], signaling an excellent fit. The Comparative Fit Index (CFI) assesses the model’s fit relative to a baseline model. At 0.991, surpassing the threshold of 0.90 [146], the model demonstrates a strong fit.

Similarly, the TLI (Tucker and Lewis’s Index of Fit) also gauges the relative fit of the model. With a value of 0.987, exceeding the 0.90 threshold [147], it suggests a good fit. The NFI (Normed Fit Index) evaluates the enhancement of the model relative to a null model. At 0.983, surpassing the 0.90 threshold [145], it indicates a good fit. Finally, the RMSEA (Root Mean Square Error of Approximation) evaluates the difference between the predicted and observed covariance matrices of the model. With an RMSEA value of 0.051, below the threshold of 0.10 [148], the model demonstrates a reasonable fit.

In summary, the CFA model exhibits favorable goodness-of-fit across multiple indices, instilling confidence in its appropriateness for the data under consideration. These findings align with established criteria for evaluating structural equation models.

4.2. Testing the Hypotheses

The hypotheses in this study are tested using Partial Least Squares (PLS), a variance-based Structural Equation Modelling (SEM) technique. PLS is chosen for its capability to simultaneously model relationships among numerous dependent and independent variables, a requirement for this research. The outcomes are detailed in the following subsections.

The hypotheses are tested by SEM. The findings are illustrated in Figure 3 and

Table 5. Structural Equation Modelling Regression weights for Social Identity.

			Estimate	S.E.	C.R.	p	R2
Purchase. Intentions	<---	Social. Identity	0.958	0.055	17.511	***	0.616
Purchase. Intention	<---	Cognitive. S.I	0.295	0.030	9.788	***	0.522
Purchase. Intention	<---	Evaluative. S.I	0.133	0.029	4.626	***	0.465
Purchase. Intention	<---	Affective. S.I	0.396	0.035	11.280	***	0.550

*** p ≤ 0.001.

below.

4.2.1. Testing the First Hypotheses

H1. 

Social identity has a significant positive effect on purchase intention.

H1.1. 

Cognitive social identity has a significant positive effect on purchase intention.

H1.2. 

Evaluative social identity has a significant positive effect on purchase intention.

H1.3. 

Affective social identity has a significant positive effect on purchase intention.

The findings illustrated in Table 5 suggest that based on the regression weights, the Social Identity exerts a notable positive impact on Purchasing Intention, evidenced by a significant path with a critical ratio value exceeding 2 and a p-value (***) below 0.05. Consequently, the first main alternative hypothesis is validated, signifying that Social Identity positively influences Purchase Intention at α ≤ 0.05. Moreover, the R² for Social Identity on Purchasing Intention stands at 0.616, suggesting that Social Identity can account for 61.6% of the variance in Purchase Intention.

Moving to sub-hypotheses, the findings show that the influence of Cognitive Social Identity on Purchase Intention is notable, as indicated by the significance of the path, with a critical ratio value exceeding 2 and a p-value (***) below 0.05 [149]. Therefore, the first alternative sub-hypothesis 1.1 is supported, suggesting that Cognitive Social Identity significantly impacts Purchasing Intention at α ≤ 0.05. Additionally, the (R²) of Cognitive Social Identity on Purchase Intention is 0.522, implying that Cognitive Social Identity can explain 52.2% of the variation in Purchase Intention.

Evaluative Social Identity exerts a substantial influence on Purchase Intention, evidenced by the path’s significance, with a critical ratio value surpassing 2 and a p-value (***) below 0.05 [149]. Consequently, the acceptance of the second alternative sub-hypothesis 1.2 implies that Evaluative Social Identity significantly enhances Purchase Intention at α ≤ 0.05. Moreover, the (R²) of Evaluative Social Identity on Purchase Intention is 0.465, suggesting that Evaluative Social Identity can explain 46.5% of the variation in Purchase Intention.

Affective Social Identity significantly impacts Purchase Intention, as evidenced by the path’s significance, with a critical ratio value exceeding 2 and a p-value (***) below 0.05 [149]. Consequently, the acceptance of the third alternative sub-hypothesis 1.3 suggests that Affective Social Identity significantly enhances Purchasing Intention at α ≤ 0.05. Additionally, the (R²) of Affective Social Identity on Purchase Intention is 0.550, suggesting that Affective Social Identity can explain 55.0% of the variation in Purchase Intention.

As indicated in Table 5 above, Affective Social Identity demonstrates the highest R² value (55.0%) concerning Purchase Intention, succeeded by Cognitive Social Identity and Evaluative Social Identity, which exhibit R² values of 52.2% and 46.5%, respectively

4.2.2. Testing the Second Hypotheses

H2. 

Source credibility significantly mediating the relationship between social identity and purchase intention.

H2.1. 

Influencer’s trustworthiness significantly mediating the relationship between social identity and purchase intention.

H2.2. 

Influencer’s expertise significantly mediating the relationship between social identity and purchase intention.

H2.3. 

Influencer’s attractiveness significantly mediating the relationship between social identity and purchase intention.

Source credibility significantly mediating the relationship between social identity and purchase intention at α ≤ 0.05.

The finding of the SEM is displayed in Figure 4 and

Table 6. Regression Weights by (SEM) for Source Credibility.

			Estimate	S.E.	C.R.	p	Effect	R2
Source Credibility	<---	Social Identity	0.703	0.025	28.093	***	0.808	0.653
Purchase Intention	<---	Source Credibility	0.550	0.057	9.727	***	0.791	0.625
Purchase Intention	<---	Social Identity	0.447	0.049	9.089	***	0.785	0.616
P.I  <---  S.C <---  S.I			-	-	-	-	-	0.685

*** p ≤ 0.001.

below.

Table 6 illustrates that Social Identity exerts a notable influence on Source Credibility, evident from the critical ratio value exceeding 2 and the p-value (0.000) being below 0.05, and the estimate value stands at 0.703. Furthermore, the effect size of Social Identity on Source Credibility stands at 0.808. Similarly, Source Credibility exhibits a notable direct impact on Purchasing Intention, as indicated by a critical ratio value exceeding 2 and a p-value of 0.000, which is less than 0.05, and the estimate value is recorded at 0.550. Moreover, the effect size of Source Credibility on Purchase Intention stands at 0.791.

Additionally, Social Identity demonstrates a substantial direct impact on Purchasing Intention, with a critical ratio value exceeding 2 and a p-value of 0.000, which is lower than 0.05, and the estimate value is 0.447. Furthermore, the effect size of Social Identity on Purchase Intention stands at 0.785. Consequently, the second alternative hypothesis is affirmed, suggesting that Source Credibility significantly mediates the original association between Social Identity and Purchase Intention at α ≤ 0.05.

The R² value, reflecting the capacity of the independent variable Social Identity (SI) to elucidate alterations in the dependent variable Purchase Intention (PI), elevated from 61.6% to 68.5% owing to the mediating influence of Source Credibility (SC).

Table 7. Regression Weights by (SEM) for Source Trustworthiness.

			Estimate	S.E.	C.R.	p	R2
Trustworthiness	<---	Social. Identity	0.796	0.033	24.406	***	0.586
Purchase. Intention	<---	Trustworthiness	0.347	0.045	7.738	***	0.550
Purchase. Intention	<---	Social. Identity	0.557	0.047	11.931	***	0.616
P.I  <---  S.T <---  S.I			-	-	-	-	0.664

*** p ≤ 0.001.

exhibits that Social Identity exerts a notable influence on Source Trustworthiness, evident from the critical ratio value exceeding 2 and the p-value (0.000) being below 0.05, and the estimate value stands at 0.796. Furthermore, the R² value of Social Identity on Source Trustworthiness stands at 0.586. Similarly, Source Trustworthiness exhibits a notable direct impact on Purchase Intention, as indicated by a critical ratio value exceeding 2 and a p-value of 0.000, which is less than 0.05, and the estimate value is recorded at 0.347. Moreover, the R² value of Source Trustworthiness on Purchase Intention stands at 0.550.

Additionally, Social Identity demonstrates a substantial direct impact on Purchase Intention, with a critical ratio value exceeding 2 and a p-value of 0.000, which is lower than 0.05, and the estimate value is 0.557. The R² value of Social Identity on Purchase Intention stands at 0.616. Consequently, the first sub-hypothesis 2.1 is affirmed, suggesting that Source Trustworthiness significantly mediates the original association between Social Identity and Purchase Intention at α ≤ 0.05.

The R² value, reflecting the capacity of Social Identity (SI) to elucidate alterations in Purchase Intention (PI), increased from 61.6% to 66.4% owing to the mediating influence of Source Trustworthiness (ST).

Table 8. Regression Weights by (SEM) for Source Expertise.

			Estimate	S.E.	C.R.	p	R2
Expertise	<---	Social. Identity	0.716	0.034	21.105	***	0.515
Purchase. Intention	<---	Expertise	0.327	0.043	7.533	***	0.507
Purchase. Intention	<---	Social. Identity	0.600	0.043	13.878	***	0.616
P.I  <---  S.E <---  S.I			-	-	-	-	0.662

*** p ≤ 0.001.

illustrates that Social Identity exerts a notable influence on Source Expertise, evident from the critical ratio value exceeding 2 and the p-value (0.000) being below 0.05, and the estimate value stands at 0.716. Furthermore, the R² value of Social Identity on Source Expertise stands at 0.515. Similarly, Source Expertise exhibits a notable direct impact on Purchase Intention, as indicated by a critical ratio value exceeding 2 and a p-value of 0.000, which is less than 0.05, and the estimate value is recorded at 0.327. Moreover, the R² value of Source Expertise on Purchase Intention stands at 0.507.

Additionally, Social Identity demonstrates a substantial direct impact on Purchase Intention, with a critical ratio value exceeding 2 and a p-value of 0.000, which is lower than 0.05, and the estimate value is 0.600. The R² value of Social Identity on Purchase Intention stands at 0.616. Consequently, the second sub-hypothesis 2.2 is affirmed, suggesting that Source Expertise significantly mediates the original association between Social Identity and Purchase Intention at α ≤ 0.05.

The R² value, reflecting the capacity of Social Identity (SI) to elucidate alterations in Purchase Intention (PI), increased from 61.6% to 66.2% owing to the mediating influence of Source Expertise (SE).

Table 9. Regression Weights by (SEM) for Source Attractiveness.

			Estimate	S.E.	C.R.	p	R2
Attractiveness	<---	Social. Identity	0.618	0.033	18.676	***	0.454
Purchase. Intention	<---	Attractiveness	0.293	0.045	6.483	***	0.445
Purchase. Intention	<---	Social. Identity	0.653	0.041	15.773	***	0.616
P.I  <---  S.A <---  S.I			-	-	-	-	0.651

*** p ≤ 0.001.

illustrates that Social Identity exerts a notable influence on Source Attractiveness, evident from the estimate value stands at 0.618, the p-value (0.000) being below 0.05, and the critical ratio value exceeding 2. Furthermore, the R² value of Social Identity on Attractiveness stands at 0.454. Similarly, Source Attractiveness exhibits a notable direct impact on Purchase Intention, as indicated by estimate value recorded at 0.293, a p-value of 0.000, which is less than 0.05, and a critical ratio value exceeding 2. Moreover, the R² value of Source Attractiveness on Purchase Intention stands at 0.445.

Additionally, Social Identity demonstrates a substantial direct impact on Purchase Intention, with estimate value of 0.653 and a p-value of 0.000, which is lower than 0.05, and the critical ratio value exceeding 2. The R² value of Social Identity on Purchase Intention stands at 0.616. Consequently, the third sub-hypothesis 2.3 is affirmed, suggesting that Source Attractiveness significantly mediates the relationship between Social Identity and Purchase Intention at α ≤ 0.05.

The R² value, reflecting the capacity of Social Identity (SI) to elucidate alterations in Purchase Intention (PI), increased from 61.6% to 65.1% owing to the mediating influence of Source Attractiveness (SA).

As indicated in results, Source Trustworthiness has the strongest mediating effect, with an R² value of 66.4%. This means that Source Trustworthiness explains 66.4% of the variation in the relationship between social identity and purchase intention. Following closely, Source Expertise and Source Attractiveness have slightly lower R² values of 66.2% and 65.1%, respectively.

5. Discussion

This study examines the impact of followers’ social identity on their receptiveness to purchase recommendations from social media influencers, drawing on social identity theory [80]. Additionally, it explores the mediating role of source credibility in this relationship, based on the source credibility model [125,126].

Focusing on female millennials in Erbil, Kurdistan Region, this research investigates their purchasing intentions regarding fashion products. Millennials, with extensive access to technology and social media, actively engage with fashion trends and brands, using clothing as a means of self-expression [76,99]. Women, in particular, exhibit higher self-consciousness about appearance and invest greater financial and psychological resources in shopping compared to men [150].

Instagram was selected as the primary platform due to its popularity among millennials and its central role in influencer marketing. This study aims to enhance understanding of influencer marketing by examining the function of social identity in shaping purchasing behaviors. Influencer marketing relies on strong community bonds between influencers and followers, where social media interactions foster distinct social identities.

5.1. The Impact of Follower’s Social Identity on Their Purchasing Intention

This study extends the social identity approach [23,81] to influencer marketing. The findings confirmed hypotheses 1, 1.1, 1.2, and 1.3, demonstrating that cognitive, evaluative, and affective social identity positively influence followers’ purchasing intentions for influencer-endorsed products. When followers perceive influencers as part of their social group, cognitive social identity enhances trust and alignment with influencer recommendations. Similarly, positive self-evaluation within the influencer’s community strengthens the impact of endorsements, increasing purchase likelihood. Additionally, emotional attachment to the influencer community (affective social identity) significantly influences purchasing decisions, as strong bonds motivate followers to support endorsed products. These results align with previous research in influencer marketing [26,74] and brand identification in tourism [151].

Explicit theoretical contribution. This study extends the influencer-marketing literature in three concrete ways. First, it integrates Social Identity Theory and source-credibility theory to model credibility as the proximal mechanism that converts social identification into purchase intention—an advance over prior work that treats identification and credibility independently. Second, it disaggregates social identity into cognitive, evaluative and affective components and shows (empirically) that these dimensions differ in predictive power for fashion purchase intention (affective > cognitive > evaluative), thereby refining SIT application to consumer choice. Third, it provides quantifiable evidence that source credibility increases explanatory power: introducing credibility as a mediator raised the model R² for purchase intention from 0.616 to 0.685 (i.e., an incremental explained variance of ~7 percentage points), demonstrating that credibility is not merely correlated but meaningfully improves prediction of followers’ fashion purchase intention. These three points—a mediated causal pathway, dimensionalization of social identity, and a demonstrated incremental explanatory gain—clarify how this work extends existing theory and empirical knowledge.

Unlike prior studies focusing on consumer-brand identification and product evaluation [82,83], this research examines customer engagement within an influencer’s social group and its impact on purchasing intention. While earlier studies emphasized interpersonal influencer dynamics [51,66], this study highlights the role of social belonging and online interactions in decision-making.

Among the three dimensions, affective social identity emerged as the strongest predictor of purchasing intention, followed by cognitive social identity, whereas evaluative social identity had the least impact. These findings suggest that emotional attachment and belongingness play a crucial role in consumer behavior [152]. Notably, this contrasts with [26], who found evaluative social identity most influential, but aligns with [151], reinforcing the significance of emotional belonging in shaping identification and purchasing behaviors.

5.2. The Mediating Role of Source Credibility

The primary contribution of this study is its examination of source credibility as a mediating factor in the relationship between social identity and purchasing intention—an aspect previously unexplored. The findings confirmed hypotheses 2, 2.1, 2.2, and 2.3, demonstrating that source trustworthiness, expertise, and attractiveness significantly mediate this relationship. When individuals identify with an influencer’s community, they are more likely to perceive the influencer as credible, thereby increasing their likelihood of adopting endorsed product recommendations.

Among the three dimensions, source trustworthiness exhibited the strongest mediating effect, followed by expertise, while source attractiveness had the least influence. This suggests that trustworthiness is the most critical factor linking social identity and purchasing behavior. Followers are more inclined to purchase endorsed products when they perceive influencer recommendations as honest and reliable.

Additionally, the findings highlight a direct impact of social identity on source credibility, indicating that followers’ perceptions of influencer credibility are shaped by their sense of belonging to the influencer’s community. This aligns with the theory of group distinctiveness, suggesting that individuals reinforce their social identity by associating with credible sources [23]. This relationship has not been previously examined.

The study also supports prior research indicating a positive relationship between source credibility and purchasing intention [10,34,68]. However, the findings contradict [153], who found no significant influence of source credibility on purchasing intention. A closer comparison shows important methodological and contextual differences that plausibly explain the divergent results. AlFarraj et al. (2021) studied followers of aesthetic dermatology influencers in Jordan (n ≈ 384) and modeled online engagement (cognitive and affective engagement) as the mediator between influencer attributes and purchase intention; their analysis found attractiveness and expertise influenced engagement and purchase intention in that health/beauty context [153]. By contrast, this study focuses on fashion influencers and female millennials in Erbil (n = 421), models source credibility (trustworthiness, expertise, attractiveness) as the mediator between social identity and purchase intention, and finds trustworthiness the strongest mediating path. These differences suggest (1) category differences: aesthetic dermatology is a health/medical-adjacent sector where expertise signals and clinical trustworthiness may be interpreted differently than in fashion (where affective and identity signals often dominate); (2) sampling and influencer coverage: AlFarraj et al. (2021) collected responses via three influencers’ followers (possible influencer-level idiosyncrasies) [153], whereas this study sample is not limited to a specific influencer(s) followers, hence broader; and (3) different mediators: engagement versus perceived credibility capture different psychological processes among consumers.

Notably, the strong impact of source trustworthiness aligns with [16] but contrasts with [154], where trustworthiness had no effect. These findings emphasize the crucial role of perceived reliability in influencer marketing and consumer decision-making.

5.3. Conclusions

This study applied social identity theory to examine how followers’ identification with an influencer’s community affects the effectiveness of influencer marketing. Two research questions guided the study, and the conceptual framework was developed based on social identity theory and source credibility theory, with purchasing intention integrated through insights from the theory of planned behavior. The model explored both the direct influence of social identity on purchasing intention and the mediating role of source credibility in shaping this relationship, particularly in the context of fashion influencers on Instagram. Based on a sample of 421 respondents, the findings confirmed that followers’ purchasing intentions are significantly influenced by their social identification with an influencer’s community, with source credibility serving as a significant mediator. All research hypotheses were supported.

The first research question examined the impact of social identity on purchasing intention. The results indicated that cognitive, evaluative, and affective social identity positively influenced purchasing intention. Notably, affective social identity demonstrated the strongest effect, suggesting that emotional connections within an influencer’s community foster greater loyalty and a stronger inclination to adopt endorsed recommendations. Emotional bonds may exert a greater influence on purchasing behavior than cognitive or evaluative factors, as they create a deeper sense of attachment to the influencer and their community.

The second research question investigated the mediating role of source credibility in the relationship between social identity and purchasing intention. The results showed that source trustworthiness, expertise, and attractiveness significantly mediated this relationship. However, source trustworthiness had the strongest mediating effect, suggesting that followers are more likely to act on recommendations when they perceive the influencer as reliable and honest. Trustworthiness, encompassing integrity and authenticity, plays a fundamental role in shaping consumer behavior, as followers who trust an influencer are more inclined to believe and follow their endorsements.

This study highlights the crucial role of community dynamics in influencer marketing, offering new insights into the effectiveness of Instagram influencers. By examining the interplay between influencers, their communities, and consumer behavior, the research provides practical implications for businesses and influencers seeking to refine marketing strategies and strengthen audience engagement. Focused on female millennials, the findings contribute to a deeper understanding of contemporary consumer trends in the fashion industry and offer valuable guidance for optimizing influencer-driven campaigns

5.4. Theoretical and Practical Implications

5.4.1. Theoretical Contribution

This study makes significant theoretical contributions by examining the relationship between millennial females’ social identity and their purchase intentions in the fashion industry. Through empirical analysis, the research identifies how cognitive, evaluative, and affective dimensions of social identity influence followers’ likelihood of adopting influencer recommendations. A key contribution lies in validating the mediating role of source credibility in this relationship, addressing a critical gap in the literature and offering new insights into influencer marketing effectiveness.

Furthermore, the study introduces a novel conceptual framework that clarifies the interplay between social identity, source credibility, and purchase intention within influencer marketing. This framework enhances the understanding of consumer behavior in the fashion industry and provides a foundation for future research across various sectors. The study also demonstrates the reliability and internal consistency of the research instruments, reinforcing the validity of its findings and highlighting the robustness of the methodological approach.

5.4.2. Practical Implications

This research offers practical implications for enhancing millennial consumers’ purchasing intentions through social identity. The findings provide valuable insights for both social media influencers and brands considering influencer marketing for fashion promotion.

Instagram’s widespread adoption among female millennials presents a significant opportunity for fashion businesses. With over two billion active users monthly [17], the platform serves as a key space for fashion trends and recommendations. Millennials actively seek influencer advice on social media and consider influencers reliable sources for purchasing decisions. Consequently, fashion brands can leverage influencer marketing to engage their target audience effectively. This study underscores the dual influence of group dynamics and interpersonal communication in shaping millennials’ responses to influencer marketing. Brands should collaborate with influencers whose values align with their target audience, fostering a deeper emotional connection and reinforcing a sense of belonging, thereby enhancing purchasing intentions.

Influencers can apply these insights to strengthen follower engagement and maximize their impact. Aligning content with followers’ values and interests fosters deeper connections, while actively engaging through comments, live sessions, and user-generated content cultivates a sense of community. Strengthening these relationships increases an influencer’s persuasive power and the effectiveness of product promotions.

Moreover, the findings emphasize the crucial role of source credibility in influencer marketing. Followers are more likely to trust and act upon recommendations from influencers they perceive as credible. Enhancing credibility requires authenticity, expertise, and visually compelling content. Trustworthiness can be established through genuine experiences, while expertise is demonstrated through high-quality, informative content. Additionally, maintaining an appealing and professional aesthetic further strengthens credibility. Recognizing the importance of credibility enables influencers to build stronger relationships with followers, increasing their impact on purchasing decisions.

Similarly, fashion marketers should carefully assess influencer credibility when forming collaborations, as credibility significantly influences consumer engagement and purchasing behavior. By selecting credible influencers, brands can enhance trust and drive greater consumer interest in promoted fashion products.

5.5. Limitations and Future Research

Despite its valuable contributions, this study acknowledges several limitations, highlighting directions for future research. First, the study focused exclusively on social media influencers within the fashion sector in Erbil, Kurdistan Region. Given the distinct marketing dynamics across industries, the findings may not be universally applicable. Future research should extend the conceptual framework to other sectors to enhance generalizability.

Second, this study examined the social identity and consumer behavior of female millennials on Instagram, limiting its applicability to other generational cohorts and platforms. Future research should explore generational differences (e.g., Gen X and Gen Z) and assess influencer marketing effects on alternative platforms such as YouTube and TikTok. Additionally, investigating male consumers’ social identity and purchasing behavior, or conducting a comparative analysis of gender-based differences, would provide a broader perspective.

Third, while this research examined the mediating role of source credibility, perceptions of influencer credibility may vary across audience segments based on gender and cultural background. A qualitative approach, employing interviews or focus groups, could offer deeper insights into followers’ perceptions, motivations, and attitudes toward influencer credibility. This would further inform the development of more effective influencer marketing strategies. In addition, while the results support a mediated path from social identity → perceived credibility → purchase intention, several boundary conditions and alternative mechanisms warrant careful consideration: (a) parasocial interaction and perceived homophily are closely related to the affective dimension measured here and could partially account for the affective-dominant result; future work should include measures of parasocial closeness and perceived similarity to isolate their unique variance. (b), platform affordances (visual vs. text-heavy platforms) and influencer type (micro vs. macro) may condition credibility perceptions.

Finally, this study focused on purchase intention as an outcome of influencer marketing. Future research should examine additional consumer behaviors, such as word-of-mouth intention, brand loyalty, and repeat purchase intention. Analyzing these alternative outcomes could provide a more comprehensive understanding of the long-term impact of social identity on influencer marketing effectiveness.