Revista Latina de Comunicación Social. ISSN 1138-5820
Purchase intention and negative response towards influence on Instagram: the effect of interaction and motivation
Yezid Alfonso Cancino-Gómez
Universidad ECCI. Colombia.
ycancino@ecci.edu.co
Gerson Jaquin Cristancho-Triana
Universidad ECCI. Colombia.
gcristanchot@ecci.edu.co
Sandra Patricia Caviedes-Caviedes
Universidad ECCI. Colombia.
scaviedesc@ecci.edu.co
How cite this article / Standard reference:
Cancino-Gómez, Yezid; Cristancho-Triana, Gerson Jaquin, & Caviedes-Caviedes, Sandra Patricia (2025). Purchase intention and negative response towards influence on Instagram: The effect of interaction and motivation. Revista Latina de Comunicación Social, 83, 1-20. https://www.doi.org/10.4185/RLCS-2025-2363
Date of receipt: 18/10/2024
Date of acceptance: 17/12/2024
Date of publication: 14/02/2025
ABSTRACT
Introduction: The study focused on determining whether users' activities on Instagram influence their purchase intention on the platform and how intention is related to the formation of preferences or distrust towards influencers due to their impact on the purchase decision. Methodology: a cross-sectional quantitative investigation was carried out in which 385 men and 648 women with an Instagram account participated. Results: 7 hypotheses are accepted and 4 are rejected. In relation to the indirect effects, two complete mediations and one partial mediation are observed. Discussion: It is evident that purchase intention is affected by interaction on social media and the negative response towards influence is determined by distrust and interaction on the platform. It was shown that user interaction influences purchase intention. The interaction and influence in the purchase is affected by negative responses towards the influences and, the motivation towards the content and the influence on the purchase intention is mediated by the negative response towards the influences and distrust. Conclusions: Instagram users show complex behavior because interaction is the only factor that directly influences purchase intention when it is induced by influencers and the reasons for use are not directly related to purchase intention, but It occurs when there is a negative response towards influence. This suggests that Colombians are willing to take risks in their purchases on the platform, overcoming the lack of credibility or distrust of influencers paid to promote a brand.
Keywords: Influence Marketing; distrust toward influencer; purchase intention; social media; digital marketing.
1. INTRODUCTION
Through influencer marketing, content creators are encouraged to involve their social media followers in the promotion and consumption of products and services of different brands (Leung et al., 2022), is one of the most relevant trends within social media (Dueñas et al, 2020), which consists in the creation and dissemination of content for the benefit of a brand that has found the ideal field of action for its dissemination in social media (Ortiz & Pérez-Curiel, 2018) and that, through influencers, seeks to attract a common target audience, being one of the most effective and least intrusive strategies of current marketing (Ortiz & Pérez-Curiel, 2018). In this way, influencer marketing has been used as an engagement strategy with different audiences (García et al., 2021), becoming a relevant tactic to build trust (Lou & Yuan, 2019; Kim & Kim, 2021) within the different digital communities as well as in brand conversations (Leung et al, 2022), becoming a strategic component of relationship marketing through "collaborative links" of brands with opinion leaders and "influencers" (Nuñez et al., 2021) that, being visible for their audiovisual contents, can be a method of provocation to purchase.
The use of influencers, instagramers, youtubers, bloggers, tweeters, etc. has become one of the most innovative ways to condition purchase decisions through the trust and credibility that these individuals create in potential consumers by creating high-quality content without excessive costs for brands (Yetimoğlu & Uğurlu, 2020). Influencer marketing has implications in leveraging the trust and bond they have established with their followers to expand the reach and impact of brands on social media (Childers et al., 2018) by creating a communication intermediary with a digital community (Zeljko et al., 2018).
The research on the effect of the influencer on the purchase intention of social media users has been extensive (Ki & Kim, 2019; Vrontis et al., 2021; Masuda et al., 2022; Martín et al., 2022; Rivera 2022) and focuses on knowing the relationship between the purchase behavior of social media users and the activities carried out by influencers towards a brand, because their actions develop an endorsement discourse towards brands, products and services, thus constituting relevant promotional support to build relationships with customers (Jin et al. 2019; Chopra et al, 2021), and at the same time, due to their reach in distributed audiences, it guarantees a focused communication both in the promotion of the product, in the direct and bidirectional response to related and potential Instagram followers (Sanz et al., 2020). These recommendations are stimuli that directly or indirectly influence purchase intentions (Aragoncillo & Orus, 2018).
Although the evidence supports the positive effect of influencers on purchase intentions, the fact that viewers perceive the relevance of advertisements in influencers' content can act in the opposite direction as a result of a sense of disappointment (Boerman, 2017; Lee & Kim, 2020). This negative reaction is also manifested in the physical and social comparison that women can experience, especially in media that focus on the use of images, such as Instagram (Engeln et al., 2020). In this way, an ambivalent attitude towards influencers is presented in relation to the intentions and behaviors of users (Conner y Sparks, 2002), but at the same time, these attitudes can change or be exchanged (Wilson et al., 2000), and that in any case generates a cognitive and attitudinal conflict through the opposing evaluations generated by his followers (van Harreveld et al., 2015).
1.1. Reasons for using social media, purchase intention and mistrust of the influencer
Social media users access these platforms for various reasons, mainly to maintain relationships and companionship, especially in generations Y and Z (Paunoska, 2020; Bowden-Green et al., 2021; Lee et al., 2023), through activities such as following friends (Lup et al., 2015), searching for information, interacting, updating (Paunoska, 2020), spending time and discovering information about the interests of other users (Banerjee et al., 2009).
Various reasons, such as multipurpose searches, are related to user responses (Lee et al., 2023), since the consumption of social media content can develop real interactions between the brand and the user (Izogo & Mpinganjira, 2024), this behavior is more noticeable in Generation Z, who respond positively to "call to action" strategies (Mude, & Undale, 2023), and a positive relationship has been found between the reasons for using the social network and its influence on purchase intention (Pant et al., 2023).
Another perspective on the reasons is the negative reaction that distrust towards the source of information or content can generate, as the influencer's media coverage with a brand can be perceived as hostile and at the same time as a source of negative influence on other users (Tsfati & Cohen, 2013, p. 12). In this way, trust is generated by the parasocial relationship, understood as the degree of similarity and attractiveness of the influencer with an audience (Ki et al., 2023). Therefore, the lack of similarity or attractiveness would negatively affect trust towards him/her.
The above aspects could lead to the development of assimilation bias behaviors when the reasons for using the social media are contrasted with the content of an influencer in whom one does not have confidence, because people are looking for reliable content that serves their own interests. This situation is seen in corporate social responsibility communications, which fail to increase public concern for the environment (Leeuwerden, 2021), as well as in health services, where users' negative experiences influence medical mistrust (Williamson & Prinks, 2023), which is greater when the content is not perceived as authentic due to brand sponsorship (Steils et al., 2022).
1.2. Social media interaction, purchase intention and influencers
The role of influencers in guiding their followers in their perceptions and actions may be one of the factors that explains the influence process from the underlying pattern of need that a follower may experience, from the dependence on information and the need to find online sources that provide useful and reliable information that can support their decision-making (Bao & Chang, 2014; Hsu et al., 2013). This interaction is based on the fact that influencers provide their followers with useful content (Bentley et al., 2021), and at the same time, they grant them credibility, which improves their perception and attitude towards them, increasing the likelihood of continuing to watch said content and influencing their purchase intentions (Ibáñez-Sánchez et al., 2022; Lee et al., 2022).
Influencers act as intermediaries of the information that consumers seek or receive, which at the same time, by filtering and disseminating a message to other people, increases the potential to influence them (Bao & Chang, 2014; Magno, 2017; Uzunoğlu & Kip, 2014). For this reason, it is important that marketing actions in social media involve influential people to deter, improve interaction, add value and increase the impact of the brand on potential customers (Ananda et al., 2016). Since an influencer is a brand promoter (Castelló & del Pino, 2015), social interaction increases in sponsored publications (Hughes et al., 2019; Rodríguez & García, 2022) in the likes mode, follower growth, visualizations, and content recommendation (Feijoo & Sádaba, 2022).
For Generation Z, social media are their preferred means of communication and information, but the level of mistrust towards them has increased due to fake news, fake accounts and content that lacks credibility when compared to reality (Childers & Boatwright, 2021; Pérez-Escoda & Esteban, 2021). This effect has also been extended to influencer content due to the excessive presence of advertising and sponsored messages (Cristancho et al., 2022; Rubio-Romero & Baron-Dulce, 2019). Therefore, for brands, the use of an influencer in corporate crisis situations can lead to negative user perceptions (Singh et al., 2020) due to the image of manipulation that their intervention can generate and, consequently, negatively affect purchase intention when commercial support motives are perceived (Aw & Chuah, 2021).
1.3. The preference towards influencer, mistrust and influence on the purchase intention
The influence process occurs because opinion leaders serve as a model through which people or consumers learn and develop beliefs, attitudes, and behaviors based on the information and actions observed (Bandura, 1977), followers acquire decisive knowledge of the brands that influencers use, receiving key information to create their personal judgments in the purchasing processes, where the success of influence marketing campaigns lies in the enormous trust that followers place on them (García et al., 2021).
The attractiveness of the source and the identification with the product are aspects related to the attitude towards the influencer, which is also related to the purchase intention (Lim et al., 2017), in this regard, both Childers et al., 2018 as Lou & Yuan, (2019) indicate that the belief in the influencer exerts a persuasive power on consumers and stimulates the purchase of brands endorsed by the content creator, this is how authenticity, knowledge, experience and potential power of influence grant him/her the designation of an opinion leader (Childers et al., 2018; Li & Du, 2011; Uzunoğlu & Kip, 2014), a condition that increases as his/her popularity increases, thus affecting the attitudes towards the brand and the purchase behavior of the followers (De Veirman et al., 2017; Djafarova & Rushworth, 2017).
The preference towards an influencer is based on the type of content he/she generates, trusts and experiences (Phung & Qin, 2018), this preference of a user towards an influencer can be formed from the perception of the attractiveness of the content source, this generates an identification link with the beliefs and behaviors of the influencer (Belch & Belch, 2004), although the preference is greater when the content is relative to the life of the followers (Vidani et al., 2023). However, for Zahrah et al. (2022), an effect between advertising skepticism and preference for disseminated messages is not evident, although there is an increasing mistrust in paid advertising of products promoted by influencers (Heatherington, 2018, cited by Ali, 2022).
Mistrust contributes to the spread of opinions by affecting the emotional relationship of individuals and the final decision-making of users (Wu et al., 2017). Therefore, mistrust is a relevant element of social relationships and is crucial in social media as it is related to the content and interactions generated by users (Chen & Zhou, 2024). Mistrust plays a more important role than trust (Kunnel & Quandt, 2016), so it is important to measure the spread of mistrust, among other aspects (Li et al., 2021; Zhou et al., 2022) that allow to obtain a characterization of the phenomenon.
1.4. The negative response to the influence
The way in which a product and/or service is positioned and presented through an influencer as a medium affects the perception, attitude and effectiveness of the message (Gill et al., 1988). Therefore, knowing the attitudes of social media audiences towards the digital content of influencers can be crucial in the development of their own consumption behavior, given the affinity of tastes, interests or lifestyles with those who represent the brand and its values. While it is recognized that users are susceptible to the indications of their preferred influencer (Colliander & Dahlén, 2011), users generate their own opinions, both positive and negative, and express these attitudes through reviews or negative comments in digital media, sometimes involving brands at some point.
These online interactions generated with negative reviews of their products and/or services are public in nature because they are available online and have an impact on the formation of negative opinions that make potential customers when reading these complaints influence the purchase decision, making the response negative (Mudambi & Schuff, 2010; Schaefers & Schamari, 2015, Standifird, 2001). It has also been observed in macro-influencers a negative purchase response when the content generates the idea of falsehood (Fainmesser & Galeotti, 2019).
2. OBJECTIVES
In accordance with the above, and for the development of this research, 3 objectives and their corresponding hypotheses are established. The first objective is to determine whether the motivation to use social media exerts an influence of preference or mistrust towards the influencer in the intention to purchase products and services promoted in the social network Instagram. This objective leads to 3 hypotheses:
H1a: Motivation to use social media influences preference for the influencer's content.
H1b: Motivation to use social media influences mistrust towards the influencer.
H1c: Motivation to use social media influences the purchase intention.
The second objective is to know if the interaction in social media exerts an influence of preference or mistrust towards the influencer in the intention to purchase products and services promoted in the social network Instagram. This objective leads to four hypotheses:
H2a: Social media interaction influences preference towards the influencer.
H2b: Social media interaction influences mistrust towards the influencer.
H2c: Social media interaction influences purchase intention.
H2d: Social media interaction influences negative reaction towards the influencer.
The third objective is to analyze whether the preference or distrust towards the influencer affects both the purchase intention or a negative response, in relation to the products and services promoted on the social network Instagram. This objective leads to the formulation of 4 hypotheses:
H3a: Influencer preference is related to influencer distrust.
H3b: Influencer preference influences purchase intention.
H4: Influencer mistrust affects negative response to influencer.
H5: Negative response to influence negatively affects purchase intention.
Figure 1 shows the proposed theoretical model with the mentioned variables and their possible relationships, to analyze their effectiveness in the context of the Instagram social network.
Figure 1. Proposed theoretical model.
Source: Own elaboration.
3. METHODOLOGY
This study was approached with a quantitative approach and descriptive in scope, given that it is intended to know both the interactions and effects of motivation and interaction in social media with the preferences in the content of influencers with mistrust and purchase intention. Therefore, it is proposed to validate the proposed model and the hypotheses through a causal model.
3.1. Sample and e instrument
The target population was men and women over 18 years old with active accounts in social media, especially Instagram, and who at the same time have indicated that they have made purchases of products promoted in social media in Colombia. Based on a probabilistic sampling design, the sample was estimated, for the criterion of the total population, the population projection of men and women over 18 years old by the National Department of Statistics - DANE (2023) for the city of Bogota, which corresponds to 6,196,825, was taken as reference, for the confidence level was used 95% and 5% error, obtaining a minimum sample of 385 subjects, however, it was possible to obtain a final participation of 385 men and 648 women, for a total of 1032.
As an instrument to collect information, a questionnaire in digital format was used, divided into three parts, the first consists of the presentation, where the treatment of personal user data is indicated, guaranteeing that these will be used only for the purpose of this research. The second part consists of 4 items (gender, age, occupation and academic training) with a nominal response, the last part corresponds to 34 items with a 5-point Likert response (1= totally disagree, 5= totally agree), which group the 6 dimensions of analysis proposed in the theoretical model. The scale of motivation to use social media was adapted from Ghaisani et al. (2017) and Kircaburum et al. (2020), the interaction scale was adapted from Ghaisani et al. The scales related to preference for the influencer's content, mistrust of the influencer, and negative reaction were adapted from Suescun (2022) to determine the effect of influencers on purchase behavior in a social network. Finally, the influence scale on purchase intention was adapted from (Abreu, 2019; Kumar, 2011; Lal & Sharma, 2021). Each of the scales used can be seen in Table 1.
Table 1. Items by dimension and authors
|
Dimension
|
Item
|
Variable
|
|
Motivation towards the use of social media (MSM)
|
My motivation for using social media is to view content of my preference
|
V1
|
|
My motivation for using social media is because it is a means of communication
|
V2
|
|
My motivation for using social media is to stay informed
|
V3
|
|
My motivation for using social media is for social purposes
|
V4
|
|
Interaction on social media (ISM)
|
I use social media to display posts and interact with my circle
|
V5
|
|
I use social media to generate interaction with the accounts I follow and that follow me.
|
V6
|
|
I use social media to Upload Photos
|
V7
|
|
I use social media to Upload Videos
|
V8
|
|
I use social media to re-post content from people I follow
|
V9
|
|
Influencer preference for content on Social Media (IP)
|
I prefer the influencer who creates educational content
|
V10
|
|
I prefer the influencer who teaches languages
|
V11
|
|
I prefer the influencer who creates content to raise awareness about the environment
|
V12
|
|
I prefer the influencer who promotes leisure, tourism and entertainment activities
|
V13
|
|
I prefer the influencer who shares art (music, tattoos, dance, drawing, photography, painting, etc.)
|
V14
|
|
Mistrust towards the influencer (IM)
|
I don't trust influencers if I know they've been paid to promote a product,
|
V15
|
|
I avoid purchasing products promoted by an influencer that are not accurately described
|
V16
|
|
I don't purchase when an influencer promotes products or services that are unrelated to the content they develop
|
V17
|
|
I don't trust influencer reviews because they are paid to promote the product
|
V18
|
|
I tend to purchase products or services without considering influencers
|
V19
|
|
I do not consider an influencer's opinion when purchasing a product
|
V20
|
|
I don't purchase if I don't think the influencer is credible.
|
V21
|
|
Negative response to influence (NRI)
|
I believe that if a product or service recommended by a content creator does not meet my expectations, I immediately stop following the influencer.
|
V22
|
|
I believe that if a product or service recommended by a content creator does not meet my expectations, I immediately stop following the brand.
|
V23
|
|
Influence on purchase intention (IPI)
|
I feel more confident if the product is recommended by an influencer.
|
V24
|
|
I have purchased products or services used by content creators because I identify with them
|
V25
|
|
I have purchased more products or services on Instagram because of an influencer's recommendation than because of advertising on Instagram
|
V26
|
|
I have actively participated in all the dynamics created by the influencers I follow on social media
|
V27
|
|
Influencers have created a purchase impulse in me on social media
|
V28
|
|
When I am looking for information about a product or service, I prefer to have it explained by an influencer.
|
V29
|
|
I have purchased products or services because of an influencer's influence
|
V30
|
|
I am more likely to purchase what an influencer is promoting when I feel I identify with him/her.
|
V31
|
|
I like to participate in contests run by the influencers I follow.
|
V32
|
|
I have purchased products or services that do not meet an immediate need based on the recommendation of a content creator on social media
|
V33
|
|
I have used discount codes when shopping on social media based on an influencer's recommendation.
|
V34
|
Source: Own elaboration.
3.2. Data analysis
As for the data analysis, a descriptive analysis was applied to the 4 items that characterize the population participating in the study, and as a starting point for the structural analysis, an exploratory factor analysis (EFA) was applied to observe the degree of grouping of the proposed items in each dimension, using the SPSS program. Based on these results, a confirmatory factor analysis (CFA) was applied to validate the grouping of each dimension with respect to the proposed items (Martínez Ávila, 2021). Finally, a causal model was developed through the bootstrapping methodology to validate the proposed hypotheses, using the Amos program.
4. RESULTS
After applying the instrument, the study participants are characterized by a higher participation of women (n=648, 62.8%) than men (n=384, 37.2%), age between 18 and 26 years (n=628, 60.9%), 27 to 43 years old (n=358, 34.6%) and over 43 years old (n=46, 4. 5%), in terms of their occupation, most study and work (n=413, 40%), work (n=390, 37.8%), study only (n=185, 17.9%) and neither study nor work (n=44, 4.3%), with basic and secondary academic education (n=288, 27.9%), technical and technological (n=448, 43.4%), professional (n=230, 22.3%) and postgraduate (n=66, 6.4%).
In the first instance, an AFE was developed (KMO=0.920; Bartlett Sphericity=p<0.0001; cumulative variance=66.49) with the total of 34 items to see their degree of correlation with each proposed factor, it was identified in the first instance that 4 variables (v5, v7, v18 and v20) obtained factor loads lower than 0.7 reason why they were eliminated from the study (Darmawan et al., 2020). Then a first CFA was performed (Chi-square=1736.0, degrees of freedom=390, P<0.0001) where it was evident that 3 variables (v8, v14 and v19) obtained loads lower than 0.7, so they were eliminated from the study. A new AFC was applied (Chi-squared=616.94, degrees of freedom=290, P<0.0001) where all factor loads obtained values at 0.7 according to the criterion of Raubenheimer (2004).
In Table 2, it is observed that as for the convergent validity, Cronbach's Alpha in the proposed dimensions obtained values between 0.688 and 0.96, being these satisfactory (Hu & Bentler, 1999), in the same way the composite reliability index (CR) in each of the proposed dimensions obtained values between 0.689 and 0.96, complying with the standards proposed by Hu & Bentler (1999), as well as the value of the average variance extracted (AVE) obtained values higher than 0.5 in each dimension. On the other hand, in Table 3, with respect to the discriminant validity, it is observed that the value of the square root of the AVE is higher than the correlations between each dimension, fulfilling the criteria of Fornell & Larcker (1981). Finally, it can be observed that the criterion of the value of the Maximum Squared Shared Variance (MSV) is fulfilled in all cases with values lower than the AVE, as well as the MaxR(h) shows values close to 1, except for IRS and RNI (Hair et al., 2010).
Table 2. Factor loadings and convergent validity
|
Dimension
|
Variable
|
Factor loading
|
Alpha
|
CR
|
AVE
|
|
Motivation to use social media (MSM)
|
V1
|
0.808
|
0.876
|
0.884
|
0.657
|
|
V2
|
0.796
|
|
V3
|
0.805
|
|
V4
|
0.831
|
|
Interaction on social media (ISM)
|
V6
|
0.723
|
0.688
|
0.689
|
0.526
|
|
V9
|
0.726
|
|
Influencer preference for content on Social Media (IP)
|
V10
|
0.848
|
0.856
|
0.857
|
0.602
|
|
V11
|
0.812
|
|
V12
|
0.713
|
|
V13
|
0.721
|
|
Mistrust towards the influencer (IM)
|
V15
|
0.816
|
0.9
|
0.895
|
0.68
|
|
V16
|
0.891
|
|
V17
|
0.808
|
|
V21
|
0.78
|
|
Negative response to influence (NRI)
|
V22
|
0.74
|
0.775
|
0.779
|
0.64
|
|
V23
|
0.855
|
|
Influence on purchase intention (IPI)
|
V24
|
0.857
|
0.96
|
0.96
|
0.685
|
|
V25
|
0.856
|
|
V26
|
0.863
|
|
V27
|
0.853
|
|
V28
|
0.848
|
|
V29
|
0.839
|
|
V30
|
0.819
|
|
V31
|
0.817
|
|
V32
|
0.808
|
|
V33
|
0.795
|
|
V34
|
0.738
|
Source: Own elaboration.
Table 3. Discriminative validity.
|
|
MSV
|
MaxR(H)
|
IPI
|
IM
|
IP
|
ISM
|
NRI
|
MSM
|
|
IPI
|
0.211
|
0.961
|
0.827
|
|
|
|
|
|
|
IM
|
0.128
|
0.903
|
0.240***
|
0.825
|
|
|
|
|
|
IP
|
0.131
|
0.869
|
0.180***
|
0.269***
|
0.776
|
|
|
|
|
ISM
|
0.211
|
0.689
|
0.459***
|
0.151***
|
0.361***
|
0.725
|
|
|
|
NRI
|
0.128
|
0.797
|
0.316***
|
0.358***
|
0.246***
|
0.308***
|
0.8
|
|
|
MSM
|
0.17
|
0.885
|
0.205***
|
0.166***
|
0.234***
|
0.413***
|
0.168***
|
0.81
|
Source: Own elaboration.
To test the hypotheses proposed in the theoretical model, the bootstrapping technique was used, with 2000 subsamples as criteria, with a confidence level adjusted to 95%. The results of the causal model (Chi-square=614.71, degrees of freedom=290, P<0.0001), indicate an explained variance for IP, IM, NRI and IPI (0.144, 0.086, 0.205 and 0.245), with the values of IPI and NRI being the most relevant. On the other hand, the goodness-of-fit indices of the model meet the criteria of Brown (2015), Escobedo Portillo et al. (2016), Hu & Bentler (1999) and Kline (2011); both in terms of absolute fit and parsimony indices, which can be observed in Table 4.
Table 4. Model goodness of fit indexes
|
Index
|
Result
|
Criteria
|
Comments
|
|
CMIN/DF
|
2.12
|
Between 1 and 3
|
Excellent
|
|
NFI
|
0.968
|
>0.90
|
Excellent
|
|
RFI
|
0.962
|
>0.90
|
Excellent
|
|
IFI
|
0.983
|
>0.90
|
Excellent
|
|
TLI
|
0.979
|
>0.90
|
Excellent
|
|
CFI
|
0.983
|
>0.90
|
Excellent
|
|
PNFI
|
0.8
|
Closer to 1
|
Good
|
|
PCFI
|
0.812
|
Closer to 1
|
Good
|
|
RMSEA
|
0.033
|
<= 0.05
|
Acceptable
|
Source: Own elaboration.
Table 5 shows the results of the proposed hypotheses, where 7 of them are accepted and 4 are rejected. It is observed that there is a weak effect with a positive significance between motivation to use social media (MSM) with preference to the influencer for content in social media (IP) (H1a, β=0.098, p<0.05) and mistrust of the influencer (IM) (H1b, β=0.089, p<0.05), but against the influence on purchase intention (IPI) (H1c, β=0.011, p>0.05) there was no significance, so H1c is rejected. On the other hand, interaction in social media (IMS) showed a moderate and significant effect in terms of influencer preference for content in social networks (IP) (H2a, β=0.327, p<0.01), influence on purchase intention (IPI) (H2c, β=0.392, p<0. 01), influence on purchase intention (IIC) (H2c, β=0.392, p<0.01), and negative response to influence (NRI) (H2d, β=0.261, p<0.01), but it has no effect on mistrust toward the influencer (IM) (H2b, β=0.045, p>0.05), so H2b is rejected.
In addition, it is observed that the preference to the influencer for the content in social networks (IP) has a moderate effect with positive significance with the distrust towards the influencer (IM) (H3a, β=0.235, p<0.01), while against the influence on the purchase intention (IPI) (H3b, β= -0.013, p>0.05) there is no significance, so H3b is rejected. On the other hand, distrust towards the influencer (DI) has a significant effect with negative response to influence (NRI) (H4, β=0.329, p<0.01) and finally, negative response to influence (NRI) has a significant positive effect with influence on purchase intention (IPI) (H5, β=0.235, p<0.01), but H5 is rejected because it was proposed that its influence is negative.
Table 5. Direct effect results
|
Hypothesis
|
Coefficient
|
Lower Limit
|
Higher Limit
|
P (sig.)
|
Comments
|
|
H1a
|
MSM → IP
|
0.098
|
0.017
|
0.175
|
0.015
|
Accepted
|
|
H1b
|
MSM → IM
|
0.089
|
0.008
|
0.174
|
0.034
|
Accepted
|
|
H1c
|
MSM → IPI
|
0.011
|
-0.067
|
0.093
|
0.738
|
Rejected
|
|
H2a
|
ISM → IP
|
0.327
|
0.24
|
0.41
|
0.001
|
Accepted
|
|
H2b
|
ISM → IM
|
0.045
|
-0.055
|
0.152
|
0.373
|
Rejected
|
|
H2c
|
ISM → IPI
|
0.392
|
0.3
|
0.493
|
0.001
|
Accepted
|
|
H2d
|
ISM → NRI
|
0.261
|
0.178
|
0.345
|
0.001
|
Accepted
|
|
H3a
|
IP → IM
|
0.235
|
0.154
|
0.319
|
0.001
|
Accepted
|
|
H3b
|
IP → IPI
|
-0.013
|
-0.085
|
0.058
|
0.748
|
Rejected
|
|
H4
|
IM → NRI
|
0.329
|
0.247
|
0.407
|
0.001
|
Accepted
|
|
H5
|
NRI → ICC
|
0.202
|
0.132
|
0.275
|
0.001
|
Rejected
|
Source: Own elaboration.
Table 6 shows the indirect effects, where it was identified that in three of them there is no significant mediation, the first one expresses that there is no significant indirect effect between motivation to use social networks (MSM) and influence on purchase intention (IPI) mediated by preference to the influencer for the content in social networks (IP) (β= -0.001, p=0.637). Second, interaction in social networks (IRS) does not exert an indirect effect with influence on purchase intention (IPI) mediated by preference to the influencer for the content in social networks (IP) (β= -0.005, p=0. 737), finally, interaction in social networks (ISM) has no indirect effect with influence on purchase intention (IPI) when mediated by both distrust of the influencer (IM) and negative response to influence (NRI) (β= 0.004, p=0.321).
Table 6. Indirect effect results.
|
Relationship
|
Coefficient
|
Lower Limit
|
Higher Limit
|
P (sig.)
|
Comments
|
|
MSM→IP→IPI
|
-0.001
|
-0.011
|
0.007
|
0.637
|
No mediation
|
|
MSM→IM→NRI
|
0.027
|
0.003
|
0.057
|
0.03
|
Full mediation
|
|
IRS→PI→IIC
|
-0.005
|
-0.038
|
0.022
|
0.737
|
No mediation
|
|
ISM→IM→NRI→IPI
|
0.004
|
-0.004
|
0.013
|
0.321
|
No mediation
|
|
ISM→NRI→ICC
|
0.066
|
0.041
|
0.102
|
0.0001
|
Partial mediation
|
|
MSM→IP→IM→NRI→IPI
|
0.002
|
0.000
|
0.004
|
0.007
|
Full mediation
|
Source: Own elaboration.
5. DISCUSSION AND CONCLUSIONS
The research aimed to understand whether user actions on Instagram, such as interaction and motivation to use social media, influence purchase intention, especially when this intention is induced by an influencer's content and outreach activities, about which the user forms a preference or mistrust that can influence both purchase intention and negative reaction toward the influencer.
The relationship between motives for using social networks and preferences for influencer content found in this research has been little explored, this relationship has been analyzed from the identification with the influencer, which puts into perspective that in social media and influencer marketing, interest in the content may be a relevant factor, partly because other research describes a direct effect of motives with purchase intention (Pant et al, 2023), but the results here do not show a direct relationship, but an effect mediated by other variables is exerted (Croes & Bartels, 2021), however, not all mediations generate purchase intention, as the existence of influencer content preference only exerts an effect on mistrust of the influencer. This suggests that users' content preferences are unrelated to influencer marketing activities.
Social media content is linked to a reference figure associated with users' social and cultural values, which makes the influencer's effect greater on their decisions (Martin et al., 2022; Rivera, 2020). However, The perception of advertising actions in contents, such as critical online comments by users (Schaefers & Schamari, 2015), creates a negative influence (Tsfati and Cohen, 2013).
A relationship between the interactions and the purchase influence is not verified, mediated by the preference of the content disclosed by the influencer, but if it is observed that the negative response to the influence mediates between the purchase intention and the interactions, it may seem incoherent, but in this case the commercial actions of the influencer demolish the arguments based on mistrust and negative perception, as happens in persuasive social influence, when a subject modifies or changes his/her opinion or behavior expecting a positive reaction from another subject (Kelman 1961, cited by Ferrer, 2021), this is also a behavior that is represented in the theory of the dual system, where the self-control mechanism is overcome by compulsive behavior (Moayery et al., 2019), and when the source is considered credible and honest, its message can exert influence by modifying a person's belief or value system (Kapitan, & Silvera, 2016), this happens even when Generation Z tends to distrust social media or commercial content (Pérez-Escoda & Esteban, 2021; Childers & Boatwright, 2021; Rubio-Romero & Barón-Dulce, 2019) or that they consider to be manipulated (Aw & Chuah, 2021). This behavior indicates that Colombian users on Instagram are willing to take some risks when shopping on this platform, confirming the findings of Ibáñez-Sánchez et al. (2022), regarding the positive effect of the use of influencers on purchase intention due to the trust attributed to them by their followers (García Rivero et al., 2021; Childers et al., 2018; Lou & Yuan, 2019).
A complex behavior of users on Instagram in relation to influencer marketing is found, in which the interaction behavior of users is the only factor that has a direct impact on purchase intention, especially when this intention has been induced by outreach activities performed by an influencer. The reasons for using the social network are not directly related to purchase intention, but purchase intention is present when there is a negative response to the influence driven by a perception of mistrust, which suggests that Colombians are prone to take risks when purchasing products through social media to overcome the lack of credibility, the perception of payment to promote a brand or the inaccurate exposure of the information of the promoted product.
Both the interaction in social media and the motives to use them generate in the user an appreciation about the preference towards the content and at the same time a mistrust towards the influencer, both aspects associated with a negative response to the influence, which harms the influencer or the brand, but does not interfere with the users being induced to purchase, since the influencers exert influence by providing information about the product or service, to evoke trust based on the recommendation rather than advertising, and even motivate the impulsive purchase.
A user's actions and motivations on Instagram trigger a response to both preference for content shared by influencers and mistrust, suggesting that users develop their attitudes once they are exposed to the posted content, but it is noteworthy that preference and distrust have no direct or indirect effect on influence on purchase intention. However, interaction mediated by preference, which is related to perceived mistrust, exerts a negative response to influence, thus disrupting the influence on purchase intention.
The present research generates new questions regarding the aspects or arguments that make people overcome mistrust and negative response to influence and still maintain a purchase intention on Instagram, what is the acceptable and unacceptable risk to decide to purchase, and whether this behavior can be presented in other social media or in other territorial groups.
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AUTHOR CONTRIBUTIONS, FUNDING AND ACKNOWLEDGEMENTS
Contribuciones de los/as autores/as:
Conceptualization: Cancino-Gómez, Yezid. Software: Cristancho-Triana, Gerson. Validation: Cristancho-Triana, Gerson. Cancino-Gómez, Yezid. Formal analysis: Cristancho-Triana, Gerson. Data curation: Cancino-Gómez, Yezid. Writing-Preparation of the original draft: Caviedes-Caviedes, Sandra. Cancino-Gómez, Yezid. Writing-Revision and Editing: Cristancho-Triana, Gerson. Caviedes-Caviedes, Sandra. Cancino-Gómez, Yezid. Supervision: Caviedes-Caviedes, Sandra. Project management: Caviedes-Caviedes, Sandra.
All authors have read and approved the published version of the manuscript: Cristancho-Triana, Gerson. Caviedes-Caviedes, Sandra. Cancino-Gómez, Yezid.
Funding: This research is part of the research project approved by the internal call for funding of the Universidad ECCI, headquartered in Bogotá with project number ID IN-08-61 entitled "Consumer Behavior in Digital Media". Starting date: 25-24-20123. End date: 30-05-2024.
Thanks: Universidad ECCI.
Conflict of interest: There is no conflict of interest.
AUTHORS:
Yezid Alfonso Cancino-Gómez
Universidad ECCI.
Yezid is trained as a Publicist and Master in Marketing, teacher, researcher and currently research director of the marketing and advertising program at the Universidad ECCI, associated with the GICEA research group, the Neuromarketing and ConsumoLab seedbeds; classified as Associate Researcher (call 894, 2021). His research activity has focused on marketing management and the development of a marketing audit procedure. Development of a new methodology to determine brand personality and the adoption of ICT in SMEs in the service sector, research on issues of responsible consumption, brand, consumer, influencing and digital marketing.
ycancino@ecci.edu.co
Índice H: 4
Orcid ID: https://orcid.org/0000-0002-1961-9052
Scopus ID: https://www.scopus.com/authid/detail.uri?authorId=57211395441
Google Scholar: https://scholar.google.es/citations?user=loVSpQQAAAAJ&hl=es&oi=ao
ResearchGate: https://www.researchgate.net/profile/Yezid-Cancino
Gerson Jaquin Cristancho-Triana
Universidad ECCI.
Gerson is an Associate professor at the Faculty of Economics and Administrative Sciences, Universidad ECCI. He holds a Master’s degree in Organizational Management from the Central University. He is a researcher in the Marketing and Advertising program and director of the ConsumoLab research group. Research interests: consumption, consumer behavior and entrepreneurship.
gcristanchot@ecci.edu.co
Índice H: 7
Orcid ID: https://orcid.org/0000-0002-2009-6893
Google Scholar: https://scholar.google.es/citations?user=Jkt-juMAAAAJ&hl=es&oi=ao
ResearchGate: https://www.researchgate.net/profile/Gerson-Cristancho
Sandra Patricia Caviedes-Caviedes
Universidad ECCI.
Sandra is a publicist from the Central University and holds a Master’s degree in Marketing from the University of Manizales. She has been a research professor associated with the GICEA research group and the ConsumoLab seedbed of the Marketing and Advertising program at the ECCI University. She has coordinated and led research processes both formative and scientific, managing academic and business projects.
scaviedesc@ecci.edu.co
Índice H: 1
Orcid ID: https://orcid.org/0000-0001-6262-7595
Google Scholar: https://scholar.google.es/citations?user=8ewHXbAAAAAJ&hl=es&oi=ao