The effect of social influence, trust, and entertainment value on social media use: Evidence from Pakistan

Figures & data

Figure 1. Research model

Figure 2. Conceptual model of mediation

Figure 3. Overview of the structured model along with values of R-squared

Note: Confidence value (t value)

Table 1. Validity and reliability of measurement scales

Constructs	Items	Mean	SD	Factor loading	p value	Cronbach alpha (α)	Composite reliability	AVE
Intention to use SNS	Q4	3.453	1.211	0.887	0.000	0.829	0.898	0.746
	Q5	3.657	1.103	0.872	0.000
	Q6	3.47	1.106	0.831	0.000
Pervasive adoption of SNS	Q7	3.255	1.138	0.810	0.000	0.793	0.865	0.616
	Q8	3.402	1.118	0.779	0.000
	Q9	3.244	1.036	0.787	0.000
	Q10	3.113	0.992	0.764	0.000
Compliance	Q11	3.408	1.05	0.832	0.000	0.710	0.838	0.633
	Q12	3.496	1.038	0.806	0.000
	Q13	3.337	1.052	0.746	0.000
Identification	Q14	3.283	0.998	0.835	0.000	0.770	0.867	0.685
	Q15	3.473	0.987	0.830	0.000
	Q16	3.374	0.965	0.818	0.000
Internalization	Q17	2.992	1.300	0.895	0.000	0.844	0.905	0.760
	Q18	2.969	1.228	0.88	0.000
	Q19	2.952	1.205	0.839	0.000
Trust	Q20	3.159	1.045	0.813	0.000	0.739	0.852	0.657
	Q21	3.13	1.091	0.819	0.000
	Q22	3.142	1.138	0.80	0.000
Attitude	Q23	3.278	1.063	0.816	0.000	0.706	0.836	0.629
	Q24	3.17	1.114	0.781	0.000
	Q25	3.289	1.052	0.781	0.000
Entertainment value	Q26	3.365	1.116	0.794	0.000	0.820	0.881	0.649
	Q27	3.425	1.159	0.839	0.000
	Q28	3.368	1.096	0.810	0.000
	Q29	3.422	1.176	0.779	0.000

Note: χ², SRMR, d_ULS, d_G, and NFI refer to Chi², standardized root-mean-square residual, squared Euclidean distance, geodesic distance, and normed fit index, respectively.

Table 2. Demographics of respondents

Category		Frequency	Percent
Gender	Male	257	73
	Female	96	27
Age	15-24	297	84
	25-34	34	10
	35-44	14	4
	More than 45	8	2
Education	Undergraduate degree	270	76
	Master’s degree	83	24

Figure 4. Strength of mediation path

Table 3. Descriptive statistics and correlation analyses

	Attitude	Compliance	Entertain-ment value	Identifi-cation	Intention to use SNS	Internali-zation	Pervasive adoption of SNS	Trust
Attitude	(0.793)
Compliance	0.428	(0.796)
Entertainment Value	0.515	0.427	(0.806)
Identification	0.614	0.543	0.473	(0.828)
Intention to use SNS	0.601	0.468	0.537	0.698	(0.864)
Internalization	−0.019	−0.068	0.128	−0.087	−0.253	(0.872)
Pervasive Adoption of SNS	0.645	0.522	0.547	0.702	0.657	−0.039	(0.785)
Trust	0.368	0.291	0.474	0.304	0.304	0.251	0.345	(0.811)

Correlation is significant at the 0.01 level (two-tailed).

Table 4. Hypothesis testing

Parameter	Estimate	SD	T Statistics	P Values	Decision
Attitude -> Intention to use SNS	0.195	0.051	3.756	0.000	supported
Compliance -> Intention to use SNS	0.032	0.041	0.729	0.466	not supported
Entertainment Value -> Intention to use SNS	0.26	0.043	5.969	0.000	supported
Identification -> Intention to use SNS	0.415	0.051	8.323	0.000	supported
Intention to use SNS -> Pervasive Adoption of SNS	0.657	0.037	17.600	0.000	supported
Internalization -> Intention to use SNS	−0.245	0.033	7.473	0.000	supported
Trust -> Attitude	0.37	0.064	5.764	0.000	supported
Quality criteria of model (fit indices of measurement model)
		Calculated values		Cutoff Values
Probability level		0.000		< 0.05
Comparative Fit Index (CFI)		0.96		> 0.900
Normed Fit Index (NFI)		0.90		> 0.900
Good Fit Index (GFI)		0.91		> 0.900
Root Mean Square Error of Approximation (RMSEA)		0.04		> 0.06

Note: *, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. χ², SRMR, d_ULS, d_G, RMS, and NFI refer to Chi², standardized root-mean-square residual, squared Euclidean distance, geodesic distance, root mean squared, and normed fit index, respectively.

Table 5. Mediation analysis

	Mediation Paths	Specific Indirect Effect	t values	p values	Remarks
H8	Trust -> Attitude -> Intention to use SNS	0.068	3.162	0.002	Do not reject

Note: Hair et al. (2017a) mentioned that the VAF would be smaller than 0.2 in the presence of a significant indirect effect (VAF < 0.2, no mediation; 0.2 ≤ VAF ≤ 0.8, partial mediation; VAF > 0.8, full mediation).

Table

Construct	Items	Source
Intention to Use SNS.	My interaction with SNSs (e.g. Instagram) is clear and understandable.	Cheung & Lee, 2010
	It is easy for me to use SNSs.
	I find it easy to get SNSs do what I want them to do.
Pervasive Adoption of SNS	I accept that SNS (e.g. Instagram) is an integral part of my social life.	Ifinedo, 2016
	My group of friends accepts that SNS is an integral part of our social lives.
	I foresee no difficulty in embracing, i.e. adopting willingly SNSs (e.g. Instagram) use.
	Adopting SNSs willingly or eagerly is important to me.
Compliance	My group of friends’ views of SNSs (e.g. instagram) use is similar to mine.	Dholakia et al., 2004; Cheung et al., 2011
	It is necessary for my group of friends to use SNSs to be accepted among peers.
	Unless my group of friends sees the benefits of using SNSs, they would see no reason to spend extra effort in using such tools.
Identification	In our interactions, my group of friends feels a sense of ownership about the use of SNSs (e.g. instagram).	Dholakia et al., 2004; Cheung et al., 2011
	My group of friends talks up the use of SNSs to other friends that have not joined.
	My groups of friends are proud of using SNSs (e.g. instagram).
Internalization	SNSs (e.g. Instagram) are important to my group of friends.	Dholakia et al., 2004; Cheung et al., 2011
	The reason my group of friends use SNSs is that such tools provide some underlying social benefits.
	My groups of friends like to use SNSs primarily because of the similarity between our values and the benefits that such tools provide.
Trust	The comments of products/services on instagram are correct.	Matos and Rossi, 2008; Fogel & Nehmad, 2009
	Comments on instagram are reliable.
	I am confident on the comments of products/services posted on instagram.
Attitude	I think using instagram is beneficial to me.	Davis, 1989; Hsu & Lu, 2007; Lin, 2007
	I think using instagram is a nice idea.
	I think instagram is helpful to our society.
Entertainment Value	Using SNSs (e.g. Instagram) provides me with a lot of fun.	Dholakia et al., 2004; Cheung et al., 2011
	I have fun using SNSs.
	The process of using SNSs is pleasant.
	SNSs (e.g. Instagram) do not bore me.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017a). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: Sage Publications.

 Google Scholar

Cheung, C. M., & Lee, M. K. (2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49, 24–30. doi:10.1016/j.dss.2009.12.006.

 Web of Science ®Google Scholar

Ifinedo, P. (2016). Applying uses and gratifications theory and social influence processes to understand students’ pervasive adoption of social networking sites: Perspectives from the Americas. International Journal of Information Management, 36, 192–206. doi:10.1016/j.ijinfomgt.2015.11.007

 Web of Science ®Google Scholar

Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing, 21, 241–263. doi:10.1016/j.ijresmar.2003.12.004.

 Web of Science ®Google Scholar

Cheung, C. M., Chiu, P. Y., & Lee, M. K. (2011). Online social networks: Why do students use facebook? Computers in Human Behavior, 27, 1337–1343. doi:10.1016/j.chb.2010.07.028.

 Web of Science ®Google Scholar

De Matos, C. A., & Rossi, C. A. V. (2008). Word-of-mouth communications in marketing: A meta-analytic review of the antecedents and moderators. Journal of the Academy of Marketing Science, 36, 578–596. doi:10.1007/s11747-008-0121-1.

 Web of Science ®Google Scholar

Fogel, J., & Nehmad, E. (2009). Internet social network communities: Risk taking, trust, and privacy concerns. Computers in Human Behavior, 25, 153–160. doi:10.1016/j.chb.2008.08.006

 Web of Science ®Google Scholar

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13-3, 319–340. doi:10.2307/249008

 Web of Science ®Google Scholar

Hsu, C. L., & Lu, H. P. (2007). Consumer behavior in online game communities: A motivational factor perspective. Computers in Human Behavior, 23, 1642–1659. doi:10.1016/j.chb.2005.09.001

 Web of Science ®Google Scholar

Lin, J. C. C. (2007). Online stickiness: Its antecedents and effect on purchasing intention. Behaviour & Information Technology, 26, 507–516. doi:10.1080/01449290600740843

 Web of Science ®Google Scholar