American Journal of Social Sciences and Humanities

Volume 5, Number 2 (2020) pp 221-229 doi 10.20448/801.52.221.229 | Research Articles

 

Impact of Trust Aspects and Value Co-Creation as Mediation on Purchase Intention in Social Networking Context

D. Asokan 1
1 Associte Professor-Department of Management Studies, BAMR, Karnataka, India.

ABSTRACT

Social Media Communication through Social Networking has become developing marketing issue of increasing popularity. This article investigates Word-of-Mouth communication through Social Networking Sites guided by the socialization framework with Purchase Intention as outcomes and Value Co-creation, Trust as antecedents. 508 participants who engaged in Word- of-Mouth communication about products through Social Networking Sites are surveyed. It confirms that the trust and Value Co-creation influences Purchase Intention positively. Electronic Word-of-Mouth communication impacts Purchase Intention directly and indirectly by reinforcing Value Co-creation with Trust. The model is used to study the main objective of determining the factors of consumer purchase intention through Word-of-Mouth communication in Social Networking Sites. These findings have significance managerial and theoretical implications.

Keywords: Consumer socialization, Word-of-mouth communication, Trust aspects, Value Co-creation, Purchase intention.

DOI: 10.20448/801.52.221.229

Citation | D. Asokan (2020). Impact of Trust Aspects and Value Co-Creation as Mediation on Purchase Intention in Social Networking Context. American Journal of Social Sciences and Humanities, 5(2): 221-229.

Copyright: This work is licensed under a Creative Commons Attribution 3.0 License

Funding : This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

History : Received: 14 February 2020 / Revised: 16 March 2020 / Accepted: 21 April 2020 / Published: 11 May 2020 .

Publisher: Online Science Publishing

Highlights of this paper

  • This article investigates Word-of-Mouth communication through Social Networking Sites guided by the socialization framework with Purchase Intention as outcomes and Value Co-creation, Trust as antecedents.
  • It confirms that the trust and Value Co-creation influences Purchase Intention positively.

1. INTRODUCTION

Consumers and marketers communication have been changed by social media (Hennig-Thurau et al., 2004; Nambisan and Baron, 2007). Millions of users daily lives with business practices are integrated by Social Media (Muratore, 2008; Okazaki, 2009) Peer groups particularly are connected using social media by adding them to network of friends, facilitating communication (Ahuja and Galvin, 2003; Zhang and Daugherty, 2009). Social media emergence prompted the change in decision making by consumers and in marketing communication (Shankar and Malthouse, 2007) . Product reviews proliferated through social media, have significant marketing impact (Hennig-Thurau et al., 2004; Trusov et al., 2010).  Such media Word-of-Mouth alters consumers information processing and increases marketing messages (Casteleyn et al., 2009). Consumer socialization, a new form on marketing strategies and consumer decision, in particular Electronic Word-of-Mouth communications through social networking has intense impacts on purchase intention (Casteleyn et al., 2009; Okazaki, 2009). People engage social media for socialization among themselves and with strangers (Lueg et al., 2006; Muratore, 2008).  Electronic Word-of-Mouth communication has got limited research study (Ahuja and Galvin, 2003; Gliem and Gliem, 2003) though it is acknowledged heavily as a key factor of consumer socialization (Churchill and Moschis, 1979). Particularly, Social Networking Word-of-Mouth communication and its impact on purchase decision by consumers has rarely been investigated (Iyengar et al., 2009; Trusov et al., 2010). To fill this gap from the perspective of consumer socialization, we investigate, consumption related word of mouth communication through Social Networking and its impacts on Value Co-Creation, Consumers Trust and Purchase Intentions.

2. LITERATURE REVIEW

2.1. Consumer Socialization through Social Media

Cognitive, affective and behavioural attitudes are affected by consumer communication as predicted by consumer socialization theory (Ward, 1974). Consumption related skills; attitudes in the marketplace and knowledge are learned by consumers through socialization process. Socialization framework outlines the learning processes and consumers role in the society. (Churchill and Moschis, 1979; Gregorio and Sung, 2010).

A cognitive development model and social learning theory offers two theoretical perspectives on understanding and predicting consumer-to-consumer information transmission. Cognitive and psychological aspects are focused by the former and the latter highlights on environmental learning sources or peers as ‘socialization agents’. Norms, motivations, attitudes and behaviors are transmitted by socialization process (Shim, 1996; Kohler et al., 2011). Consumer socialization processes among non-family members has been explained by consumer socialization theory (Ahuja and Galvin, 2003; Gregorio and Sung, 2010; Taylor et al., 2011). Product placement behaviors and attitudes are influenced by circles of friends and acquaintances. Peer communication predicts the relationships of product placement behaviors and attitudes.

Social Networking Sites act as an agent of consumer socialization and provide virtual space to communicate through the Internet (Lueg and Finney, 2007; Muratore, 2008; Zhang and Daugherty, 2009; Kohler et al., 2011) .  Consumer socialization among peer is encouraged by three conditions. First, instant messages through electronic communication and learn knowledge and skill by interaction with other members. Second, consumer use social media websites for consumption related decisions (Lueg et al., 2006). Third, it facilitate vast information and evaluations quickly (Gershoff and Johar, 2006; Taylor et al., 2011). Socialization factors reveal that Electronic Word-of-Mouth communication influence and convert them into shoppers. Based on the theory of socialization we establish a model to explain Word-of-Mouth communication’s through social learning process and its outcomes.

2.2. Electronic Word-of-Mouth, Institutional Trust, Trusting Belief and Co-Creation of Value

User generated Word-of-Mouth Communication through social networking has impact on Consumers trust and influences others (Dellarocas, 2003) to buy products of the firm.  Views or performance rating behavior for a firm can be provided by prior consumers through their consumer-supplier relationship. These EWOM can be used by potential consumers in trusting the firm and their products. Positive EWOM produces positive belief about the product eminence and the service rendered. Hence, it generates and develops consumers’ trust and thereby increasing intention to buy Kim et al. (2009). Also, negative EWOM reduces purchase intention as well as the consumer belief.

Prior studies reports the EWOM generated in online forms like emails, forum (Xia and Bechwati, 2008)  blog and virtual community etc (Chan and Ngai, 2011). Websites and their influencing  intention to buy. Prahalad and Ramaswamy (2004a) have developed the notion of value co-creation. The product value or a service value is not only formed by a supplier or manufacturer alone but it’s also generated by the consumers by applying their knowledge and expertise (Vargo et al., 2008). The value co-creation is developed by the emotional engagement (Payne et al., 2008) of consumers with the brand. Most of the previous studies are conducted in the area of online retailing/commercial websites /shopping etc., but a few studies are found to be in exploring the Social Networking. Secondly, most of them examined on technical aspects such as secure payment methods, website quality factors, graphics and number of clicks etc.,. Thus, in depth study on additional aspects like Social Networking Word-of-Mouth communication (EWOM), value co-creation and consumers’ trust seems reasonable. Finally, studies conducted formerly concerning Value Co-Creation and consumers’ trust are limited.

3. RESEARCH METHODOLOGY

Primary data for the research is collected using questionnaire and surveyed in Chennai, India. The sampling unit is an individual having an account with social networking sites. The questionnaire has two sections, namely section-A and section-B.  Section-A contains demographic profile of the respondents such as gender, age, occupation, education, monthly income, etc., Section-B includes 23 questions about the theoretical framework and responses to latent variables or research factors Table 3. It  comprises of five questions for Trusting Belief, four questions for Electronic Word-of-Mouth; Disposition to Trust; Institutional Based Trust and three for Purchase Intention; Value Co-Creation.

The measurement items/operational variables are revalidated and adapted from prior studies i.e., Electronic Word-of-Mouth is measured with items from Chu and Kim (2011) institution Based Trust, Disposition to Trust and Trusting Belief items are developed from McKnight et al. (2002a) value Co-Creation is modified from Leuthesser and Kohli (1995); the validated scales and Purchase Intention is transformed from Wang et al. (2012). Latent variables are measured using seven point Likert scale representing “1” denotes strongly disagree and “7” denotes strongly agree. The questionnaire is validated by a survey with 20 respondents as pilot study. Structural equations modeling (SEM) is used with maximum likelihood estimation (MLE) to analyze the research data. First step is to assess the indicators/operational variables as it represents latent variable. The CFA is used to measure the reliability and to implement the measurement model in determining the factor loading of the latent variable. The depiction of the model by See-To and Ho (2014) with the latent variable “EWOM" can be used for other latent constructs as well,

E1=λ1EWOM+eE1;   E2=λ2EWOM+eW2;   E3=λ3EWOM+eW3;   E5=λ3EWOM+eW5

Where,

E1, E2, E3, E5 = EWOM Indicators; λ1, λ2, λ3 and λ5 = Factor Loadings; eE1, eE2, eE3 and eE5 = Error indicators.

To institute the dependent & independent association of the latent variables, a Regression Analysis is used with the following model:

PIN= β1EWOM+ β2ITR+ β3TRB+ β5VCC+e

Where,

PIN= Purchase Intention.

EWOM=Electronic Word-of-Mouth.

ITR=Institutional Trust.

TRB=Trusting Belief.

VCC=Value co-creation.

e=Disturbance Error.

β1...β5 = Regression parameters.

The following hypothesis is developed based on the above discussion of Word-of-Mouth communication and its interaction with diverse facets of Trust and Value Co-Creation.

H1.a Word-of-Mouth Communication in Social Networking Sites impacts Institutional based trust.

H1.b Word-of-Mouth Communication in Social Networking Sites impacts Trusting belief.

H2.a Word-of-Mouth Communication impacts Purchase Intention in Social Networking.

H2.b Trusting Beliefs of a brand’s product and its Word-of-Mouth Communication in Social Networking impacts Purchase Intention.

H3.a Word-of-Mouth Communication impacts Value co-creation in Social Networking.

H3.b Trusting beliefs of a brand’s product and its Word-of-Mouth Communication in Social Networking impacts Value Co-Creation.

H3.c Value Co-Creation process impacts Purchase Intention.

4. RESULTS AND FINDINGS

4.1. Descriptive Analysis

Demographic profiles of 508 survey respondents are illustrated in Table 1. Approximately 56.8% of participants are frequent users of the social networking site Facebook and 17.1% have used Google Plus; 10.1% used LinkedIn, 7.1% of the participants have used Twitter and 8.9% used other social networking sites. There are 369(72.6%) males and 139(27.4%) females. Most of the respondents, 305 (60%) are in 17-26 age category and 120(31%) respondents indicates an annual of income of 2.4 lakhs category. Among them, 335(65.9%) with bachelor’s degree, 130(25.6%) belongs master’s degree, 10(2%) completed high school and 33(6.5%) belongs other categories of education including diploma. Ample number 388(76.4%) of respondents are employed, 120(23.6%) of them are students. Regarding social networking site usage, approximately 15.6% of the participants spent more than 3h on their chosen social networking site per day, and 10.1% spent 2-3h per day, 60.2% spent 1-2h per day, and 14.2% spent less than an hour per day. The demographic characteristic related to the total Chennai population represents a higher level of young and educational respondents.

Table-1. Demographic profile.

Items
Categories
Frequency
%
Cumulative (%)
Gender
Male
369
72.6
72.6
Female
139
27.4
100
Age
17-26
305
60
60
27-36
158
31.1
91.1
37-46
33
6.5
97.6
≥47
12
2.4
100
Education
High School
10
2
2
Bachelor
335
65.9
67.9
Master
130
25.6
93.5
Other
33
6.5
100
Occupation
Government
61
12
12
Private
310
61
73
Other
137
27
100
Annual Income
≤ 1.20
30
8
8
(Lakhs)
1.21-2.40
120
31
39
2.41-3.60
106
27
66
3.61-4.80
36
9
75
≥4.81
96
25
100
Social Networking Sites
Facebook
383
56.8
56.8
(Multiple choice)
Google Plus
115
17.1
73.9
LinkedIn
68
10.1
84
Twitter
48
7.1
91.1
Other
60
8.9
100
Frequency of use per day
<1hr
72
14.2
14.2
1-2hr
306
60.2
74.4
2.1-3hr
51
10.1
84.4
>3hr
79
15.6
100


4.2. Reliability Analysis and Item Statistics

Mostly, Inter reliability on variables is measured using Cronbach’s Alpha Test for reliability. It‘s value is more than 0.70 for an instrument to have satisfactory level of reliability (Gliem and Gliem, 2003; Sekaran and Bougie, 2009). In this study of six research latent variables, Cronbach’s Alpha coefficient value is bigger than 0.70 for all the variables under study. Validity and reliability of the research instrument can be evaluated through item reliability, convergent validity & discriminant validity. Convergent validity can also be evaluated through item loadings.

Table- 2. Reliability test.

latent variables
AVE
Composite reliability
R square
Cronbachs alpha
Communality
Disposition to trust
0.53
0.82
-
0.70
0.53
Institutional trust
0.55
0.83
0.21
0.73
0.55
Purchase intention
0.67
0.86
0.23
0.76
0.67
Trusting belief
0.53
0.85
0.39
0.78
0.53
Value Co-creation
0.66
0.85
0.33
0.74
0.66
EWOM in SNSs
0.62
0.87
-
0.80
0.62

Finally, discriminant validity is evaluated by assessing the variance extracted (AVE), which also indicates the given constructs dissimilarity. In the table, √AVE is highlighted diagonally by excessing the correlations value of the constructs.

Table-3. Item statistics and measurement model results.

Factors
Loading
eWOM in social media (M=4.14, SD=1.90)                                                                                              
When I consider new products, I ask my contacts on the social network sites for device.
0.69
I like to get my contacts’ opinions on the social network sites before I buy new products.
0.78
I feel more comfortable choosing products when I have got my contacts opinions on them on the social network sites.
0.79
My contacts on the social network sites pick their products based on what I have told them.
0.58
Disposition to trust (M=4.08, SD=1.63)                                                                                                          
Most of the time, people care enough to try to be helpful, rather than just looking out for themselves.
0.56
In general, most folks keep their promises.
0.65
I think people generally try to back up their words with their actions
0.64
Most people are honest in their dealings with others.
0.59
Institutional trust (M=4.31, SD=1.71)                                                                                                             
I am comfortable making purchases on the internet.
0.63
The internet has enough safeguards to make me feel comfortable using it to transact personal business.
0.63
I feel confident that encryption and other technological advances on the internet make it safe for me to do business there.
0.65
In general, the Internet is now a robust and safe environment in which to transact business
0.63
Trusting belief (M=4.19, SD=1.68)                                                                         
Overall, Social network is very knowledgeable about products.
0.60
In general, Social network is very knowledgeable about products.
0.61
Social network is truthful in its dealings with me.
0.65
I would characterize social network as honest.
0.69
Social network would keep its commitments.
0.66
Value co-creation (M=3.91, SD=1.68)
Myself and the personnel I interact with on the social network side give each other ample notice of planned changes that might impact our purchase decisions.
0.75
Myself and the personnel I interact with on the social network side would discuss any plans that might change the nature of our purchase decisions.
0.68
Myself and the personnel I interact with on the social network side take the time needed to discuss new ideas
0.68
Purchase Intention(M=4.63, SD=1.88)
How would you rate your purchase intention
Unlikely/Likely ?             
0.77
Uncertain/certainty?    
0.65
Definitely not/ Definitely
0.72
Notes:
Model-fit-statistics: Chi-square = 496.47, df= 219,  GFI=0.92, AGFI=0.90,IFI=0.93,
CFI=0.93,  TLI=0.91, PGFI=0.73, PNFI=0.76, RMSEA=0.05, PCLOSE=0.49

Table-4. Discriminant validity test

Latent variable
1
2
3
4
5
6
1. Disposition to Trust
0.77
2. Institutional Trust
0.33
0.78
3. Purchase Intention
0.40
0.36
0.82
4. Trusting Belief
0.51
0.38
0.33
0.79
5. Value Co-Creation
0.44
0.36
0.42
0.45
0.80
6. eWOM in SNSs
0.39
0.37
0.36
0.40
0.51
0.79

4.3. Factor Analysis Results (CFA)

Factor Analysis results are shown in Table 3. Data analysis program, AMOS version 21 can be used to exclude the indicators having less than 0.5 factor loading.

4.4. Linear Regression

The regression analysis is used to establish the association between EWOM, Institutional Trust, Disposition to Trust, Value Co-Creation and Trusting Belief as independent variables along with the dependent variable Purchase Intention. The regression analysis output is shown below.

Figure-1. Estimation of variables.

From the coefficient matric of this integrated model, EWOM has impact on institutional trust and is significant with p-value  p=.001,  disposition to trust has impact on institutional trust and is significant with p-value p= .001, EWOM in  media has impact on trusting belief  and is significant with p-value p=.017, disposition to  trust has impact on trusting belief and is significant with p-value p=0.001, institutional trust has impact on trusting belief and is significant with p-value p=.001, EWOM in social networking has impact on value co-creation and is significant with p-value p=.001, trusting belief has impact on value co-creation with p-value p=.001 and has impact on purchase intention with significant p-value p=.009, EWOM has direct positive impact on Purchase Intention with significant at p-value p=.037 and value co-creation impacts purchase intention with  p-value p=.015.

Hence, seven hypothesizes are accepted. It can be concluded that electronic Word-of-Mouth, institutional trust, disposition to trust, value co-creation and trusting belief have significant positive impact on consumer Purchase Intention. The projected coefficient indicates the linear association between the predicted variable (purchase intention) and five other predictor variables (electronic word-of-mouth, institutional trust, disposition to trust, value co-creation and trusting belief). The coefficients reflect the degree of association between the constructs.

The research findings are reliable with hypothesis which states that the electronic Word-of-Mouth through social networking, value co-creation, trust impacts Purchase Intention.

5. CONCLUSION

It can be concluded that purchase intention has direct impact by electronic Word-of-Mouth and have indirect impact by different facets of trust and value co-creation. This research reinforces our understanding of EWOM and its impact on purchase intention through Social Networking Sites which echoes the research study of Cheung and Thadani (2010). In particular, this study is initial one on EWOM influencing purchase intention with empirical justifications. The study has the practical inferences along with limitations to discourse for further research.

First, grounded on the result of the empirical study, E-commerce practitioners (B2C) can gain acumen to build up their brand images and better utilize the social media resources. Second, based on the empirical results this research will help practitioners to improve co-creation of value with the product users and improve a better approach in using social networking platform. Third, the research gains acumen for practitioners in understanding consumers on repeated purchases by applying the notion of value co-creation which increases the revenue and sales volume for the firms. Finally, the marketing messages can better be spread with the help of social networking sites to develop positive EWOM on products and services.

We declare that the model validity and some other constructs in TAM model (like perceived usefulness) may have interfaces with existing constructs in the model. However, our ample literature review already includes those vital constructs in the model.

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About the Authors

D. Asokan
Associte Professor-Department of Management Studies, BAMR, Karnataka, India.

Corresponding Authors

D. Asokan

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