Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
A STUDY ON IMPACT OF FACEBOOK BRAND-RELATED USER GENERATED
CONTENT (UGC) ON CONSUMER RESPONSES
ASADULLAH LAKHO1.
SHAHZEB ZULFIQAR2.
MUHAMMAD ADNAN3.
FAIZAN UL HAQ4,
KEHKASHAN NIZAM5
ABSTRACT
The purpose of this study is to propose and test a model that investigates the impact of brand related Facebook UGC on consumer responses.
Research objectives include: Understand the impact of brand related UGC with respect to consumer emotional & cognitive responses.
Investigate the process by which these cognitive and emotional responses are impacted, and Test whether homophily and brand involvement have any moderating impact on these proposed SOR Model has been used to drive the proposed model for this study (Mehrabian & Russell, 1.
The SOR model studies the impact of environmental elements on consumer responses.
there responses may include behavior, emotion and cognition.
Data collection for this research will be done through online survey questionnaires.
These questionnaires will be shared online to potential respondents.
These questionnaires will also contain a link to dummy Facebook Fan Pages that will work as stimuli, then after being exposed to these stimuli will the respondent be asked the required questions.
The respondents will be selected through Purposive Sampling who have the characteristics of being a regular Facebook user and have exposure to E-Commerce.
The data of this research will be analyzed through SPSS and AMOS to confirm reliability and validity of our constructs and to test our model.
Keywords: Social Commerce.
Stimuli Organism Response Model.
Social Media.
E-commerce.
S-O-R.
SEM-PLS.
Homophily.
Brand Involvement.
Social Networking Sites.
SNS.
Purchase Intention,Consumer Responses.
Facebook JEL Codes: D91.
L81
INTRODUCTION
The purpose of this chapter is to discuss the background of social media in the retail industry and how social media is used by customers.
The Objective and Significance of this research are also discussed.
BACKGROUND
With the adaption of new technology, the retail industry is on the verge of changing rapidly.
Technological Advancements have played a major role in improving operations and customer relations in retail industry (Accenture.
There has been a drastic change in consumer experience due to technology.
There have been a significant reduction in barriers towards adopting a technological tool as a part of lifestyle, and that has resulted in technology users of many ages and backgrounds (Accenture, 2.
, this usage of digital medium allows consumers to take full control of their purchasing experiences.
Getting information about any product and purchasing has become easier then According to a google survey (Google, 2.
, about cell phone user by consumers, 82 % of 1,507 shoppers looked for product information via their smartphones in-between shopping and 90% used smartphones the compare prices and product information prior to shopping.
With the latest technologies changing consumer behavior in the retail industry, the impact of social media is also There are many social media platforms that enable consumers to interact and share experiences, which impact their buying intention (Tuten, 2.
These social media platforms include Social Networking Sites (SNS.
, wikis, online forums, blogs, micro blogs, and other content sharing online platforms.
SNSs allow people to search for PhD Scholar.
Iqra University,Karachi.
Pakistan, asadullah.
lakho27@gmail.
Digital Marketing Manager.
GroupM.
Karachi.
Pakistan MBA/MPhil.
Iqra University.
Karachi.
Pakistan PhD Scholar.
Iqra University.
Karachi.
Pakistan PhD Scholar.
Iqra University.
Karachi.
Pakistan Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
and find people of similar likings and mindset, and enable social communication (Joinson, 2.
Wikis are type of SNS that are designed to allow all customers to collectively participate and update information on wikis (Heinonen.
Micro-blogs and blogs have content shared in a free writing style by customers and organizations both.
Other platforms may include content sharing platforms that may include content that is visual in nature .
ideos and picture.
(Heinonen, 2.
Everybody is able to participate in these social networking sites and share related content (Tuten.
RESEARCH OBJECTIVE Social media platforms allow participants to share their views about certain brand.
this content containing their experiences has an influence on other participants as well.
This impact need to be examined and understood.
There has been limited research conducted on the impact of user generated content (UGC) on consumer intention and behavior.
so, this research aims to conduct a research on the impact of brand related UGC on customer response.
Understanding the role of UGC is very crucial, as it is considered to have a significant impact on customer response and it also presents a great challenge because lack of research has led to lack of understanding in controlling its impact.
Empirical research is also important for better understanding of how Consumers are using UGC, resulting in a shift of focus from market to consumers.
This addresses the impact of UGC and its extent of impact due to which consumer response is influenced.
All social media platforms differ in the way they enable participants to get and share information with others via UGC.
This research specifically focuses on Facebook, as it is one of the most used social media platforms and provides a variety of ways to share and consume UGC.
A broad approach is taken to understand the impact of UGC on consumer This broad approach involves testing of SOR consumer response model (Mehrabian & Russell, 1.
For this research, the main focus is on the investigation of impact of brand related UGC on customer response specifically on Facebook a eWOM.
So, the two main characteristics of eWOM were also included as moderation variables that are homophily and brand involvement from the theory of communication (Hovland et al.
, 1.
SIGNIFICANCE
Based on the given questions, cover both theoretical and practical aspects.
This research has added theoretical understanding towards the impact of UGC on consumer response.
This consumer response will help brands to better understand the best way to use brand related UGC.
Studying the role of homophily and brand involvement will help the marketers to better understand how brand related UGC impacts consumer response.
Following this research, the marketers are able to better understand how UGC impacts different characteristics of consumer behavior.
this would allow them to use UGC in a more strategically effective way.
Prior work done on eWOM was followed to build a theoretical standing, then the study extended this theory into social media context and examining the impact of eWOM on consumer response specifically in social media perspective, then a process was documented to explain this impact (Kim, 2.
The proposed model was the first to present this process of brand related UGC impacting consumer response derived from S O R Model (Kim, 2.
LITERATURE REVIEW
The literature review covers the theoretical framework being tested, the related theory for the framework, and hypotheses being tested in this research (Kim, 2.
THEORETICAL BACKGROUND
STIMULUS ORGANISM RESPONSE (SOR) FRAMEWORK
The SOR model was initially designed to depict the impact of environment on behavioral responses .
ognitive and The SOR model depicts that the relationship between its three main constructs in linear with the mediating role of organism between stimuli and response (Kihlstrom, 1.
Stimulus: In SOR model, the construct stimuli relates to the physical environment that influences an individualAos internal (Eroglu et al.
, 2001.
Sherman et al.
, 1.
In regard to this model, many stimulus have been tested.
for example, color (Bellizzi et al.
, 1983.
Bellizzi & Hite, 1.
, lights (Baker et al.
, 1.
, music (Baker et al.
, 1.
, as factors that influence a consumers behavior.
Organism: In SOR model, organism is the construct that mediates the relationship between stimuli and response (Mehrabian & Russell, 1.
Mehrabian & Russell in 1974 proposed that organism involves pleasure, arousal and Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
Pleasure represents happiness, arousal represents state of being active, and dominance is to state of not restrictions (Brengman & Geuens, 2004.
Mehrabian & Russell, 1.
Based on many follow-up researches, arousal and emotion have been found to be emotional responses as dominance has little or no empirical evidence (Donovan & Rossiter, 1.
Response: The response in SOR model represents the final outcome reactions (Bagozzi, 1.
Figure 1.
SOR model (Eroglu et al.
, 2.
HYPOTHESES DEVELOPMENT
The focus of this research is on the impact of brand related UGC on Facebook on consumer behavior.
So, the hypotheses have been designed in this context.
Anjella J.
in 2014 investigated the same hypotheses on the basis of which, a grounded level theory was built in UGC domain (KIM, 2.
This research attempts to retest them in a different context to authenticate the credibility of the theory previously generate.
ORGANISMIC RESPONSES TO BRAND-RELATED UGC: S-O RELATIONSHIPS
H1.
Consumer emotional responses are influenced by UGC related to Brand.
H1-a.
Pleasure is influenced by UGC related to Brand.
H1-b.
Arousal is influenced by UGC related to Brand.
H2.
Perceived Information Quality responses are influenced by UGC related to Brand.
BEHAVIORAL RESPONSES TO BRAND-RELATED UGC: O-R RELATIONSHIPS
H3.
Information Pass-along is positively influenced by emotional response.
H3-a.
Information Pass-along is positively influenced by Pleasure.
H3-b.
Information Pass-along is positively influenced by Arousal.
H4.
Information Pass-along is positively influenced by cognitive response.
H5.
Impulse buying is positively influenced by emotional response.
H5-a.
Impulse buying is positively influenced by Pleasure.
H5-b.
Impulse buying is positively influenced by Arousal.
H6.
Impulse buying is positively influenced by cognitive response.
H7.
Future-purchase intention is positively influenced by emotional response.
H7-a.
Future-purchase intention is positively influenced by Pleasure.
H7-b.
Future-purchase intention is positively influenced by Arousal.
H8.
Future-purchase intention is positively influenced by cognitive response.
H9.
Brand engagement is positively influenced by emotional response.
H9-a.
Brand engagement is positively influenced by Pleasure.
H9-b.
Brand engagement is positively influenced by Arousal.
H10.
Brand engagement is positively influenced by cognitive response.
MODERATION
H11.
Relationships between consumer internal states and UGC is moderated by Homophily.
H11.
Relationships between consumer internal states and UGC is moderated by BrandInvolvement.
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
Figure 2.
Conceptual Framework
METHODOLOGY
PHILOSOPHICAL UNDERPINNING OF RESEARCH
For online buying, customer intention to purchase is researched to be impacted by user generated content (UGC) or customer feedback on online platforms.
these platforms include all social media platforms where customers may engage in a discussion regarding their opinion on an online purchase of a product or service.
These discussions provide feedback, comments, ratings, and customer ranking etc.
This research focuses on understanding the impact of customer feedback on social media platforms on consumer buying The data is collected through online questionnaire forms.
The participants are social media users, who have experience with conducting purchase online.
We follow Post-positivism theory for this research.
Positivism argues that only observable and measurable entities are a part of knowledge and reality, and everything beyond that is impossible.
That means that human emotions and thoughts would also be considered as not a part of human decision-making process, as we canAot directly observe and measure these.
Online survey makes it possible to generate a simulation that properly represents the phenomenon of interest.
As the main objective of this research is to investigate the impact of UGC in SNS on Consumer response, an exposure to an online UGC is expected to impact the response from consumer and so a stimulus was also introduced during online questionnaire survey.
Because of this, online survey was the right methodology for this research.
On the other hand.
Post-positivism follows the concepts of critical realism, which states that there is much more the reality that what we can observe.
This means, that emotions and thoughts are also a part of the reality and are observable and measurable to an extent.
Now these observations do not represent reality itself but Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
help us in understanding it, as post-positivism argues that fully understanding reality is not possible.
RESEARCH DESIGN
This study was conducted through an online Questionnaire Survey.
The purpose of this survey is to get quantitative behavioral responses from the respondents that will allow the researchers to make interference regarding the respondents using this data (Creswell, 2.
World-wide, the rate of online survey method is growing significantly (Comley, 2.
Compared to all traditional methods, online surveys allow much larger reach, quicker response rate, and much more cost effectiveness (Sue & Ritter, 2.
This type of surveys allow researchers to accumulate large data and easily transfer it to any other research tool (Duffy et al.
, 2.
This method of online survey is also proven to be convenient for respondents.
This way, the questionnaire can be filled at time and place of choice and convenience.
Because the online questionnaire survey is filled in privacy and in the absence of the researcher, their possible biases of the researcher is eliminated (Duffy et al.
, 2005.
Duffy, 2.
INSTRUMENT DEVELOPMENT
DEVELOPING A VISUAL-STIMULI
In order to examine the impact of UGC on consumer response, stimulus Facebook SNS fan pages were made along with relevant postings.
Fan pages allow customers of a certain brand to share their experiences of that brand and interact with each other in-order to make an informed decision regarding a purchase.
Fan page is a platform where firms can directly communicate with its customers and consumers.
because of this reason, the concept of eWOM can also be analyzed through this medium (Chen et al.
, 2.
There are many fan pages of Facebook that allow customers to post their experiences with the brand and respond through comments to other customers.
QUESTIONNAIRE DEVELOPMENT
Online questionnaire that has been used for this research has been adapted (Kim, 2.
SAMPLING
All respondents of this research are active users of Facebook, one of the most well-known and used SNSs for the purpose of sharing experiences.
According to Smith .
, more than 65% of internet users are also Facebook users (Wildrich.
Comparing all age brackets, the most concentration is found in the age bracket of 18 Ae 27.
Based on these research base facts.
Criteria for respondent was to be a Facebook user and of age above 18.
Purpose sampling technique was used.
DATA COLLECTION
Online questionnaire survey is being used to gather data from respondents.
The questionnaire will be circulated to university students of 3 well-known universities in Karachi city.
The questions are 7 Ae Scale Unipoler likert Scale.
For gathering demographics, there are open ended questions in order to get a deeper insight into respondentsAo background.
DATA ANALYSIS
In order to test our proposed model.
SPSS and AMOS are being used for statistical analysis of collected data.
Descriptive and frequency analysis are conducted on SPSS to determine the demographic characteristics.
Independent sample Ttest is being used in this study to analyze the difference of brand awareness between the two brands being analyzed.
For testing validity and reliability, correlation, reliability tests, and factor analysis are conducted.
Structural equation modeling (SEM) is being used in this data analysis as it allows simultaneous examination between multiple independent and dependent variables.
SEM is being used here for analyzing direct and indirect paths.
ANALYSIS
BRAND AWARENESS INDEPENDENT T-TESTS
Table 1: Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means Sig.
Sig.
-taile.
Equal variances Equal variances not assumed Mean-Differ Std.
Error- Differ (Stylo m = 6.
Borjan m = 2.
t = 59.
587, df = 371, p = .
This shows that brand awareness level between the 2 brands is significantly different.
One brand has high brand involvement and other has low brand involvement.
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
PILOT TEST: UGC CONTENT DIMENSIONS
Table 2
Construct
Items Min RM1
RM2
UGC Message RM3
EM1
EM2
EM3
Max Mean Std.
This confirms that UGC item stimuli are good for use to be used as stimuli for this research.
PILOT TEST: EFA OF RELIABILITIES
Construct
UGC
No.
of Items Table 3 % of Variance CronbachAos Alpha Eigenvalue The cronbachAos alphas show that the constructs have a strong convergent reliability.
This is apilot test done from first 50 responses.
DEMOGRAPHICS
Table 4
Description Frequency Gender
Women
Men
Age
55 and up Marital Status
Married Divorced Single Education High school or less Technical school
Some college College graduate MasterAos degree Household Income
Under 20,000 Rs
$20,000- $39,999
$60,000-$79,999 89 16.
$80,000-$99,999 63 11.
Over $100,000 54 10.
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
FACEBOOK ACTIVITIES
Table 5 Characteristic Frequency Frequency of Facebook Use Continuously Multiple times/day Once/day Couple of times/week Once/week Occasionally Missing Reasons for Use Stay in touch Expression Making connections General Information Surveillance Entertainment Keeping in touch with people Number of Brands Following None 100 or over Missing Number of Fashion Brands Following None 100 or over Missing Created UGC related to brand Posting Yes Missing UGC related to brand Posting Site Brand fan pages Personal wall page Type Narrative form Photos of consumption Likes (AulikingAy a bran.
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
RESULTS: T-TESTS
Construct
Items BI1
BI2
BI3
BI4
BI5
BI6
PA1
PA2
PA3
PA4
PA5
IB1
IB2
FP1
FP2
FP3
FP4
FP5
BE1
BE2
BE3
BE4
BE5
BE6
HM1
HM2
HM3
HM4
Mean T-test Style Borjan .
f = .
Brand Involvement Information Pass-along Impulse Buying Future Purchase Intention Brand Engagement Homophily Table 6 Construct & Items Style T-test f = .
PL1
PL2
PL3
PL4
PL5
PL6
AR1
AR2
AR3
AR4
AR5
AR6
IQ1
IQ2
IQ3
IQ4
RM1
RM2
RM3
EM1
EM2
EM3
BI1
BI2
BI3
BI4
BI5
BI6
Mean Borjan Pleasure Arousal Information Quality UGC Message Brand Involvement The difference between the t-test values for two brands is quite close.
This signifies that items used it these constructs are all valid.
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
NORMALITY OF PRIMARY DATA
Table 7
Items BI1
BI2
BI3
BI4
BI5
BI6
PA1
PA2
PA3
PA4
PA5
IB1
IB2
FP1
FP2
FP3
FP5
BE1
BE2
BE3
BE4
BE5
BE6
PL1
PL2
PL3
PL4
PL5
PL6
AR1
AR2
AR3
AR4
AR5
AR6
IQ1
IQ2
IQ3
IQ4
RM1
RM2
RM3
EM1
EM2
EM3
HM1
HM2
HM3
HM4
Mean Std.
Skewness Kurtosis Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
RELIABILITY OF MEASURES
Table 8
UGC
Construct
UGC
No.
of Items CronbachAos AlphaCoefficients The cronbachAos alphas show that the constructs have a strong convergent reliability.
CORRELATION OF VARIABLES
Table 9
757** 1
491** .
527** .
496** .
UGC
**.
Correlation is significant at the 0.
01 level .
-taile.
The results showed that correlation between PA and BI exceeded .
85, however the two variableswere included in the model as response variables.
The high correlation between these two variables does not create estimation problems in SEM.
GOODNESS-OF-FIT STATISTICS FOR ITEM SETS
Table 10 Construct Full Item Set No.
of Items Model Fit Stats.
Arousal X2 = 298.
df = 9 p = .
CFI = .
Information X2 = 182.
Quality df = 5 p = .
CFI = .
X2 = 231.
df = 10 p = .
CFI = .
Reduced Item Set No.
of Items Model Fit Stats.
X2 = 121.
df = 5 p = .
CFI = .
X2 = 68.
df = 2 p = .
CFI = .
X2 = 71.
df = 3 p = .
CFI = .
Goodness of fit tells you if your sample data represents the data you would expect to find in the actual population.
A structural analysis was conducted using the maximum likelihood estimation method.
The results from the Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
structural model are presented.
The structural model exhibited a good fit.
CFI Improved.
X2 reduced closer to 0.
RELIABILITY
Table11
Construct
UGC
CronbachAos AlphaCoefficients No.
of Items Reliability improved after reduction of 4 items.
MEASUREMENT MODEL EVALUATION: STANDARDIZATION LOADINGS
Table 12 Construct No.
of Items Standardized Loadings .
in -ma.
UGC 80 - .
93 - .
89 - .
91 - .
70 - .
82 - .
87 - .
93 - .
80 - .
95 - .
An indicator that almost perfectly reflects the latent variable .
, " Brand-related UGC influences pleasure") thus should very highly correlate with the latent variable "PL" (Would expect at least .
Other indicators that are conceptually more distant from the supposed latent variable could result in a lower loading.
RESULTS: MEASUREMENT MODEL
PAIB FPBE
PLAR
IQ UGC
Reliability 553** 1 521** .
527** .
500** .
532** .
557** .
502** .
Table 13
UGC
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
CFA: MEASUREMENT MODEL SPECIFICATIONS
Figure 3
DISCRIMINANT VALIDITY OF MEASUREMENT MODEL
Table 14
UGC
UGC
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
RESULTS: STRUCTURAL MODEL (HYPOTHESES)
f = 499, p = 0.
RMSEA = 0.
CFI = 0.
CMIN = 597***.
CMIN/df = 1.
NFI =0.
Table 15
Effects Estimate PL_1 AR_1 <--<--- UGC_1 UGC_1 *** *** IQ_1 <--- UGC_1 *** BE_1 <--- PL_1 PA_1 <--- PL_1 IB_1 <--- PL_1 FP_1 <--- PL_1 BE_1 <--- AR_1 PA_1 <--- AR_1 IB_1
<---
AR_1
FP_1
<---
AR_1
BE_1
<---
IQ_1
PA_1
<---
IQ_1
IB_1
<---
IQ_1
FP_1
<---
IQ_1
MULTIPLE-GROUP MODERATION TEST
Table 16 Regression Weights: (Homophily_high - Default mode.
Estimate PL <--AR <--- UGC
UGC
IQ <---
UGC
Regression Weights: (Homophily _low - Default mode.
Estimate PL <--AR <--- UGC
UGC
***
***
IQ <---
UGC
***
Regression Weights: (Brand_Involvement_high - Default mode.
Estimate PL <--AR <--- UGC
UGC
***
***
IQ <---
UGC
***
Regression Weights: (Brand_Involvement _low - Default mode.
Estimate PL <--AR <--- UGC
UGC
***
***
IQ <---
UGC
***
Lakho.
Zulfiqar.
Adnan.
Ul Haq.
, and Nizam.
A Study on Impact of Facebook Brand-Related User Generated Content (UGC) on Consumer Responses.
Bulletin of Business and Economics, 11.
, 1-15.
https://doi.
org/10.
5281/zenodo.
SUMMARY OF HYPOTHESES TESTING
Table 17 Hypotheses Results Pleasure is influenced by UGC related to Brand.
Supported Arousal is influenced by UGC related to Brand.
Supported Perceived Information Quality responses are influenced by UGC related to Brand.
Supported Information Pass-along is positively influenced by Pleasure.
Supported Information Pass-along is positively influenced by Arousal.
Not Supported Information Pass-along is positively influenced by cognitive response.
Not Supported Impulse buying is positively influenced by Pleasure.
Supported Impulse buying is positively influenced by Arousal.
Supported Impulse buying is positively influenced by cognitive response.
Not Supported Future-purchase intention is positively influenced by Pleasure.
Not Supported Future-purchase intention is positively influenced by Arousal.
Supported Future-purchase intention is positively influenced by cognitive response.
Supported Brand engagement is positively influenced by Pleasure.
Supported Brand engagement is positively influenced by Arousal.
Supported Brand engagement is positively influenced by cognitive response.
Supported Relationships between consumer internal states and UGC is moderated by Supported Homophily.
Relationships between consumer internal states and UGC is moderated by Brand Not Supported Involvement.
CONCLUSION
Future research can address some of limitations in this research.
The proposal was done is a certain context of branded UGC on Facebook page.
So, the findings are not generic but context based.
The research in future can consider using different context in terms of product or service, social media platform, or different type of social media content.
so the model could be changed and validated as per need based on future research.
The same research can be done on a broader scale of products.
As per the hypotheses analysis, the moderating impact of homophily is found to be significant interms of influence on online purchase decision making.
For the case of brand involvement, the impact in this case or context seems to be insignificant.
The findings also show that there are many situational factors that contribute in collective impact on UGC on purchase intention.
The main focus of this research is the influence of branded social media content or UGC is a positive aspect.
Future research can focus more on the negative aspect of the branded UGC in thesame Focusing on negative aspects will provide us with more concrete findings.
So, future research should focus on negative eWOM in the same context as this research.
REFERENCES