4.3 Hypothesis test with SEM approach
4.3.4 Moderating Effects
In the one-way ANOVA, p-value presented different genders of the audiences had different e-WOM. Therefore, the gender was employed as a moderator variable to examine the moderating effect. Chi-square difference test is adopted to perform the overall model comparison between groups (Bollen and Long, 1993). Empirical results illustrated that χ2 within these two sub-groups were 347.608 and 460.678 (df = 127; Chi-square difference=113.07), and their degrees of freedom difference smaller than 1. Thus, gender promised to a moderator variable for 113.07>χ!.!",!! .
From the results of Table 9, the path from the PK to CB showed no
Table 8
Empirical result of serial mediation effects
Effects Contents Estimate p-value Confidence interval
Case 1: PK à CB à EWOM
Note. PK is persuasive knowledge; TPP is third-person perception; AFF is affection;
CB represents coping behavior; EWOM is e-word-of-mouth; NPE is narrative persuasive effect.
significance in both groups. The p-values of other paths from the AFF to CB, from the CB to e-WOM and from the CB to NPE were all significant. As to the path from the TPP to CB, the female group revealed greater significant p-value than the male group. Furthermore, the estimate of the path from the TPP to CB in the male group (0.325) was higher than that of in the female group (0.497). The estimate of the path from the AFF to CB in the male group (0.593) is greater than that of in the female group (0.454).
The main paths of these two groups were different. In the male samples, the primary path was from the AFF to NPE through CB (AFF-CB-NPE). A different path was shown in the female samples. The primary path was from the TPP to NPE through CB (TPP-CB-NPE).
5. Conclusions
The empirical results in our augmented CB model support four of our hypotheses. Namely, that TPP and AFF shaped CB. However, PK provided a non-significant result (H1). This study found that participants responded to an SF post made by a brand through TPP and AFF rather than PK, indicating that the responses of individuals are determined through self-related assessment and self-emotional status rather than an understanding of the SF post. Consistent with the ELM, self-related criteria (e.g., TPP and AFF) trigger the motivation of individuals and further enhance their engagement. This approach led the participants to deal with the information through the central path, thus influencing CB through the Instagram SF. While PK represents comprehension of a message sent by a brand, such knowledge does not appertain to self-related characteristics but to object-oriented understanding and reaches a limited degree of motivation. This message-processing mechanism leads individuals to tackle information through the peripheral path, and this has little impact on CB.
Therefore, TPP and AFF lead to different results for CB as compared to PK.
An understanding of the SF post made by brands did not have an effect on subsequent reactions. Chen (2018) suggested that an awareness of a commercial effort had little influence on the responses of Instagram audiences since they
Table 9
Model comparison between groups in t-value
Path Male Group Female Group
Estimate t-value p Estimate t-value p
PK CB 0.059 0.362 0.717 0.048 0.263 0.792
TPP CB 0.325 2.618 0.009** 0.497 3.136 0.002**
AFF CB 0.593 6.274 *** 0.454 6.653 ***
CB EWOM 0.860 15.429 *** 0.863 17.304 ***
CB NPE 0.999 24.526 *** 0.996 18.745 ***
Note. χ2/df= 2.737 (male); 3.627 (female).
were accustomed to the ubiquitousness of promotion-oriented information. The subtle innate character of the messages affected audience receptivity. The level of comprehension of the SF post was not viewed as a significant matter.
Kruglanski and VanLange (2012) contended that personal relevance contributes to motivation.
The evaluations by individuals of the influence messages have on themselves and others affect their responses to the SF posts made by brands.
Ham and Nelson (2016) agreed that personal rather than social CB is shaped by TPP. This observation has been supported by social penetration theory. The Instagram SF is a platform where users can present private information to those with whom they have reached a certain level of intimacy. In particular, users’
responses to the SF posts shown by brands tend to be based on their judgements of a post’s influence on themselves and others. The sensory awareness of the usage of the SF by brands shapes the audience’s CB. The AIM indicates the involvement of emotion and mood in tackling messages. Entertainment is viewed as one of the main reasons for the use of the Instagram SF. It can be assumed that audiences’ responses to posts in the SF are influenced by feelings. In other words, individuals would prefer to make emotional or affective responses in their appraisals of confrontational situations or events. Decisions are often reached through a combination of external information and internal cognition. In our
study, the audience’s CB urrounding the brands’ usage of the SF shaped the related descriptions that were dispatched on the Instagram website. Each type of CB shows a different type of evaluation of a subject.
As for the academic contributions of this study, the previous relevant literature has explored the causal relationship between PK, TPP, and CB or between e-WOM and CB. AFF had not been included as an antecedent variable of CB, and NPE had not been regarded as a consequence variable of CB.
Therefore, a research gap in the existing literature had formed. This provides the main academic contribution of this study. We then proposed three routes for the persuasion procedure―PK, TPP, and AFF―to highlight the drivers of CB in the Instagram SF; that is, the cognitive learning factor, the cognitive processing factor, and the cognitive appraisal factor, respectively. The empirical outcomes of our augmented CB model support most of the hypotheses. TPP and AFF influence CB in the Instagram SF (H2a and H3a). However, PK displays the opposite outcome (H1a). Based on the ELM, high and low engagement with information is influenced by motivation (Petty and Cacioppo, 1986). These results support the ELM in that the peripheral paths (TPP and AFF) obviously tend to influence CB in the Instagram SF; however, the central path (PK) does not influence CB. Thus, the higher the number of respondent reactions, the more likely it is for positive or negative comments to go viral. The audience’s CB influences psychological status regarding the Instagram SF. The following details reveal additional information.
As for practical contributions and managerial implications, the audience’s CB with the SF posts made by brands also has an influence on purchase behavior.
When individuals share an SF post, the shared values have a positive effect on trust (Wu et al., 2010), which is related to purchase intention (Hajli, 2014). With an extension of the theory of planned behavior (Pavlou and Fygenson, 2006), purchase behavior has been found to be affected by purchase desire intensity.
Using the “see more” option is related to psychological and reminiscence effects and has been explained as an interest in an issue or object (Ashcroft and Hoey, 2001). Liking is related to recall (Mehta and Purvis, 2006). Impressive memory
has a considerable effect on memory retrieval (Hamilton, 2015). CB, which halts or expands the flow of information, is related to the awareness effect. The levels of information flow represent the levels of exposure, which have a positive relationship with awareness (Gibs and Bruich, 2010). In addition, does “how they cope” have a positive influence on “the effects of the SF post” or not? The consequential variables can include NPE and e-WOM. The relationship between the CB regarding the Instagram SF, e-WOM, and NPE is worth exploring in the future.
Further findings of this study illustrate that CB has a significant influence on e-WOM and NPE in the Instagram SF. Thus, the greater the number of respondent responses, the more likely it is for positive or negative comments to go viral. The audience’s CB influences their psychological status concerning to the Instagram SF. As for the impact of CB on e-WOM, an audience’s CB refers to a personal evaluation regarding an issue or message based on self-perception theory (Bem, 1967). Namely, the attitudes of individuals toward an event result from their actions and behaviors, developing a psychological status encompassing satisfaction or dissatisfaction. As noted by Shaikh et al. (2018), the satisfaction of individuals exerts an effect on e-WOM. As for the impact of CB on NPE, the sharing of these SF posts has an effect on purchase behavior.
When users share a SF post, the shared values generate a positive effect on trust (Wu et al., 2010), which is linked to purchase intention (Hajli, 2014). Based on an extension of the theory of planned behavior, purchase behavior has been found to be affected by purchase desire intensity. The use of the “see more”
option in the Instagram SF has been linked to psychological and reminiscence effects. It has been employed to indicate an interest in an event or object.
Preference is related to recall. Impressive memory has a considerable effect on memory retrieval (Hamilton, 2015). CB, which halts or expands the flow of information, has a connection with the awareness effect in the SF. The degree of information flow indicates the degree of exposure, and that enjoys a positive causal relationship with awareness in due course.
For a more comprehensive understanding, future studies should also
compare the effects of the Instagram SF on multiple social media platforms.
According to Statista (2017), Adidas was included in a study on the statistical ranking of various types of industries. The statistical findings of the current study indicate a degree of representativeness; however, narrowing the scope of the study would be an option for a more detailed discussion. A survey could analyze the use of the Instagram SF by a specific industry. It is recommended that advanced analytics be used in future research. In a future study with a sufficient budget and time, a sample of 1,000 participants would be appropriate for decreasing the likelihood of bias.
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