Keywords

Instagram Beauty Influencers.

Introduction

The digitalization and the rise of social networks have changed the old way of doing marketing in recent years Aswathy & Vishnu (2020) and the role of consumers in this digitalisation process has also evolved. In fact, thanks to the interactive nature of social media, consumers are increasingly using these tools to gather information about the products and services on which they base their decisions Casaló et al. (2020). As a result, the consumer of this era has become a “consumer actor” (Medioni and Bouzaglo, 2018, p. 116).This latter has increasingly expressed his distrust of the traditional strategies of publicity (Barreda et al., 2015; Schivinski & Dabrowski (2016); Schuiling, 2017) and before making the purchase decision, he refers to social media to look for the information. These tools have occupied a dominant place in business strategies and have become a crucial communication channel for sharing opinions and recommendations and exchanging between consumers, real-life shopping experiences Sokolova & Kefi (2019).

This change has created new opportunities as some internet users have become opinion leaders and reference called influencers (Zhu et al., 2015; Susarla et al., 2016) whose opinions can influence consumer behaviour Sokolova & Kefi (2019).

In a context where a number of consumers refer to the opinions of influencers before making the purchase act, this research seeks to identify and understand the attitude of Instagram users towards the recommendations of beauty influencers by identifying its determinants and its effect on the purchase intent of the recommended products.

Literature Review and Research Hypotheses

The marketing of influence began as an offline strategy using thought leaders such as journalists (Brown and Hayes, 2015), however, today, attention has shifted to the digital influencer (Sammis et al. 2016, p.7), describing influence marketing as “the art and science of engaging influential people online to share brand messages with their audiences”. Its principle lies in exploiting ordinary people as advocates for brands in online communities where consumers are easier to find (Belch and Belch, 2011). According to Sudha & Sheena (2017), influence marketing draws its value from three sources including the scope of the influencer (measuring audience size), relevance (producing original and effective content), and resonance (the number of activities that an influencer generates by posting content). Digitalization and social networks have created new opportunities with a large number of influencers or bloggers have emerged on Instagram which, among other platforms, has shown the most notable growth, reaching more than one billion monthly active users in 2018 (Medioni and Bouzaglo, 2018 ; Tech Crunch, 2018).

Freberg et al. (2011, p.90), define these influencers as “a new type of independent third party endorser that shapes public attitudes through the bias of blogs, tweets and the use of other social media.” These influencers are likely “to create original, creative and authentic content” (Marrone and Gallic, 2018 p. 858).

Instagram and Youtube are the social networks that bring together the most popular influencers (Medioni and Bouzaglo, 2018, p. 121). Nevertheless, the value of influence marketing is seen, in particular, on the social network of Instagram which enjoys “extraordinary growth” as a social network and a marketing channel (Kim et al., 2017; Serra-Cantallops et al., 2018; Rietveld et al., 2020).

Similarly, “in 2019 and 2020, Instagram is still the preferred platform of marketers for influence marketing (advertisers and agencies) for posts and stories” (Asselin, 2020). In fact, brands use Instagram not only as an advertising medium, but also as a platform to better reach the target audience thanks to influencers (Belanche et al., 2019). Companies have found that these influencers are effective in disseminating information about new products and trends to the public (Jin et al., 2019). As a result, Instagram has become the preferred social network for companies looking to apply an influential marketing strategy (Sanz-Blas et al., 2019).

Whether on social networks or on other platforms, influencers produce content and engage the consumers through several devices: posts and sponsored articles, contest games, placement of brand products and gifts, and this in order to create a favorable attitude that will in turn translate into a purchasing intention Amel et al. (2017).

Determinants of Consumer Attitudes Towards Influencers’ Recommendations

The perceived usefulness, here, indicates the benefits that consumers expect to derive from the use of recommendation, including “time saving, access to additional information and diverse ideas on the product, etc.” (Negra et al., 2008). Many previous studies have confirmed that perceived usefulness positively influences attitude in the context of recommendations (Casalo et al., 2011; Riquelme & Saeid (2014). Hence, our first hypothesis is stated as follows:

H₁: The perceived usefulness of Instagram bloggers’ recommendations positively influences the female consumer’s attitude towards these recommendations.

The benefits of using a recommendation refer to its ability to help the consumer collect information on the characteristics, functions, prices, quality and effectiveness of the product (Lee and Ma, 2012). Previous research has confirmed that there is a positive and meaningful relationship between perceived benefits and consumer attitudes towards bloggers’ recommendations (Lee and Ma, 2012; Ing and Ming, 2018). Furthermore, our second hypothesis states Alalwan (2018):

H₂: The perceived benefits of female Instagram bloggers’ recommendations positively influence the female consumer’s attitude towards these recommendations.

The quality of information reflects the relevance, sufficiency (Park et al., 2007; Cheung et al., 2008), objectivity, persuasion (Park et al., 2007; Zhang et al., 2014), timeliness and added value (Wang and Strong, 1996) of the information. The quality of information has been proved to be crucial in forming supportive attitudes Erkan & Evans (2018); Ing and Ming, 2018). We start from this fact to state the following hypothesis Lee & Eastin (2020):

H₃: The quality of information provided by female Instagram bloggers positively influences the female consumer’s attitude towards these recommendations.

Credibility is defined by Tseng and Fogg (1999) as “the degree to which an individual can perceive the recommendation as credible, true, or based on real facts.” It was confirmed that credibility is positively related to the attitude towards the female influencer’s recommendations Djafarova & Rushworth (2017); Sokolova & Kefi (2019). So, the fourth hypothesis is proposed as follows:

H₄: The perceived credibility of female Instagram bloggers positively influences the female consumer’s attitude towards the recommendations of these bloggers.

In our context, trust is defined as the perceived credibility and benevolence of an influencer AlSaleh (2017). It has been demonstrated that trust positively affects consumers’ attitudes in the context of recommendations (Hsiao et al., 2010; Hsu et al., 2013; AlSaleh (2017). Thus, our fifth hypothesis states:

H₅: The female consumer’s trust in Instagram female bloggers positively influences her attitude towards the recommendations of these bloggers

The Impact of The Attitudes Towards The Female Influencers’ Recommendations on The Intent To Purchase Recommended Products

Attitude is defined as “the positive or negative orientation of the consumer towards a product or a brand” (Assael, 1987). The intent to purchase refers to the extent to which a consumer thinks that a blogger’s recommendation could improve their knowledge of a product or a service (Hsu et al., 2013). Several studies have revealed the positive impact of the attitude on purchase intent (Ha and Janda, 2012; López et al., 2014 ; Lim et al., 2017). Besides, our final assumption is as follows Figure 1 and 2:

H₆: The attitude towards female Instagram bloggers’ recommendations positively influences the purchase intent of recommended products/ services.

Finally, the conceptual model for this study is as follows:

Method

An online survey was conducted, the link of the questionnaire was sent through Instagram, to users subscribed to the influencers. Thus, the participation in our questionnaire was done on a voluntary basis. The respondents were contacted from comments on publications of product recommendations (cosmetics, accessories, clothing ...), quizzes, collaborations with brands, tutorials, etc. We defined our sample as a female audience, present on Instagram. The "snowball" collection method was also used. In total, we collected 222 questionnaires of which 212 were retained for the final survey.

The survey was conducted online, during three months (March, April and May 2020). In total, we collected 222 responses, 212 of which correspond to our target population. Indeed, among the responses obtained, we had to exclude a number of responses: those that did not match our sampling criteria : anyone who did not have an Instagram account and/or did not follow influencers.

The descriptive analysis revealed that the majority of respondents (79.7%), are young women with an age range between 18 and 29 years. These analyses confirm that younger internet users dominate Instagram usage. The majority of the sample are female students (43.4%). Female employees (34%) and high school girls (16%) also represent a significant portion of the sample. In addition, it was observed that 91% of the respondents consult Instagram several times a day. 59.9% of the respondents claim that they have already purchased at least one product recommended on Instagram Hermanda et al. (2019).

In order to measure our variables, we were inspired by existing measurement scales in the literature Riquelme & Saeid (2014); Lee and Ma ,2012; Sokolova & Kefi (2019); Park et al., 2007) where all items are measured by the five-point Likert scale ranging from "Strongly Disagree" to "Strongly Agree".

For data processing, we used two statistical software programs: IBM SPSS Statistics for the purification of the measurement scales through an exploratory factor analysis (EFA) and SmartPLS for the evaluation of the internal and external model and the testing of the hypotheses through a confirmatory factor analysis (CFA).

Result

Measurement Model Test

The results of the analysis of the factorial contributions show that the reliability indices are satisfactory: the Cronbach Alpha values vary between 0.710 and 0.832, reflecting a good reliability of the scales Chaovalit (2014).

The results of Table 1 show that the values of the average variance extracted (AVE) for all the constructs are higher than the recommended threshold of 0.5 as they varied from 0.573 to 637. We also note that the composite relaibility (CR) values for all constructs range from 0.839 to 0.882, which exceeds the recommended threshold of 0.7 ((Hair et al 2012) and proves their internal consistency Table 1.

Table 1 Convergent Validity Of Constructs
Constructs	CR	AVE
Perceived usefulness	0.842	0.573
Perceived profits	0.839	0.567
Quality of information	0.859	0.606
Trust	0.871	0.575
Perceived credibility	0.882	0.599
Attitude	0.875	0.637
Purchase intent	0.863	0.602

In addition, as shown in Table 2, all of the square roots of the AVE of each construct are higher than the correlations between it and the other constructs and range from 0.753 and 0.798. Thus, all constructs of the model meeting the criteria of Formel and Larcker and confirming the existence of a reasonable degree of discriminant validity. The results show that the model tested meets all the criteria required to evaluate the structural model Toukoumidis et al. (2021) Table 2.

Table 2 The Discriminant Validity
	Attitude	Perceived profits	Trust	Perceived credibility	Purchase intent	Quality of information	Perceived usefulness
Attitude	0.798a
Perceived profits	0.246	0.753b
Trust	0.347	0.145	0.758c
Perceived credibility	0.386	0.297	0.244	0.774d
Purchase intent	0.446	0.284	0.365	0.344	0.776e
Quality of information	0.401	0.230	0.282	0.311	0.302	0.778f
Perceived usefulness	0.314	0.295	0.269	0.222	0.248	0.242	0.757g

Structural Model Test

For the evaluation of the structural model we used three indices. Table 3 shows that all R2 are greater than 0.1 and hence attest to the significance of the model. The analysis of Q2 for all constructs shows positive values . Our model, therefore, has predictive validity. The GOF we obtained is of 0.384 and shows a good overall quality of the model Ing & Ming (2018) Table 3.

Table 3 Quality Of The Model
Constructs	R2	Q2
Attitude	0.299	0.173
Purchase Intent	0.199	0.113

In order to test our hypotheses, we used the PLS Boostrap technique, which allowed us to confirm all the hypotheses except the one relating to the profits received Constine (2018) Table 4.

Table 4 Relationship Tests
Hypotheses		Value t	Value p	Decision
H1	Perceived usefulness → attitude	2,084	0,038	Confirmed
H2	Perceived profits → attitude	0,625	0,532	Rejeted
H3	Quality of information → attitude	3,216	0,001	Confirmed
H4	Perceived credibility → attitude	3,135	0,002	Confirmed
H5	Trust → attitude	2,493	0,013	Confirmed
H6	Attitude → Purchase intent	7,263	0	Confirmed

Discussion

Our analyses show that the attitude towards recommendations is positively influenced by the perceived usefulness and credibility as well as the quality of the information and trust. This influence is confirmed by previous research (such as: Riquelme & Saeid (2014); AlSaleh (2017); Ing and Ming, 2018; Sokolova & Kefi (2019) Balagué & Fayon (2016).

Our results confirm that the female Instagram user perceives the female influencers’ recommendations as useful. This result can be explained by the fact that female consumers think that the recommendations help them reduce their uncertainty before making a purchase decision. It has also been shown that the quality of information positively influences their attitudes towards recommendations. This means that the attitude of the female consumer towards the female bloggers’ recommendations tends to be more favourable when the quality of information is objective, credible, comprehensible, clear and contains the sufficient reasons to support the opinions (Park et al., 2007). Also, the present study confirms the positive influence of trust on the attitude. This trust can be explained by the social media management of the female influencer. Through stories and live show, she sees herself honest, transparent and therefore trustworthy. In addition, credibility has been found to positively influence attitude. The more the female influencer is perceived as expert, effective in her work and active on her profile, the more credible she is seen Sokolova & Kefi (2019).

The study has also found that the attitude in turn positively and significantly influences the purchase intent of the recommended products. Instagram female influencers are increasingly becoming a reference to determine whether products are worth buying or not.

Regarding perceived benefits, no effect of this concept was identified on attitudes toward recommendations. Although our respondents considered recommendations useful, they did not perceive them as beneficial. This result can be explained by negative experiences with recommendations. When the consumer follows a recommendation and buys the product, she may be disappointed after use, if its quality and functionality do not conform to those mentioned by the influencer. Therefore, when the quality of the product does not meet expectations, the person may consider the recommendations as not beneficial.

A double observation was at the origin of the interest in the topic of the research. The first was about the consumer enthusiasm for the use of social media. The second concerned the rise and power of female influencers that could affect the consumer’s relationship with the brand.

The objective of this research was to study the determinants of the female Instagram user’s attitude towards female influencers’ recommendations of cosmetic products. The results obtained in our study highlight the importance of the perceived usefulness and the quality of the information of the recommendations, the trust and the perceived credibility of the female influencer in forming a positive attitude and leading to an intention to purchase the recommended products. From a managerial perspective, this study shows that companies need to collaborate with female Instagram influencers in order to generate positive attitudes, have more followers and trigger more sales (Booth and Matic, 2011; Colliander and Dahlén, 2011). By adopting a strategy of influence, companies must involve female influencers more in events as well as in storytelling.

The credibility of the female influencer must be taken into consideration since credibility in an online environment is fragile and subscribers can leave their community quickly. Thus, before entrusting its reputation, the company must study the female consumers’ perception of the female influencer in question (Gangloff, 2019). This is not about identifying the right female influencer according to the company’s awareness, goals and interests (Gangloff, 2019). In this way, the female influencer’s base of subscribers is not important enough as her reputation, image and expertise.

For female influencers, they need to spend more time responding to feedback. They must participate in the creation of content Abidin (2016) and be active by visiting, for example, brand stores and showing that they really try the products they recommend. The female influencer has to work on her own reputation, manage her publications of collaborations and not share many products of the same category for the risk of being not very credible.

Today, the marketing of influence has become a crucial strategy to increase awareness, strengthen consumer relationships, reach more consumers in a short time, trigger sales, etc (Kaplan and Haenlein, 2010). Therefore, the female bloggers’ recommendations seem to be a strategic and promising tool to increase sales and awareness and to guide opinions.

Conclusion And Managerial Implications

Our study has, however, some limitations related to its specific focus on a female audience. This may limit the generalizability of the results to other audiences. It is possible in future research to take other determinants of attitude towards recommendations into consideration, such as the congruence between the brand image and the image of the blogger, the reputation and the number of followers.

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Received: 01-Sep-2022, Manuscript No. AMSJ-22-12501; Editor assigned: 02-Sep-2022, PreQC No. AMSJ-22-12501(PQ); Reviewed: 16-Sep-2022, QC No. AMSJ-22-12501; Revised: 23-Sep-2022, Manuscript No. AMSJ-22-12501(R); Published: 01-Nov-2022