Driving forces of social media and its impact on tourists’ destination decisions: a uses and gratification theory

Figures & data

Figure 1. Conceptual framework.

Table 1. Respondents’ profile.

Variables	Category	Frequency	Percentage (%)
Gender	Male	278	65.12
	Female	150	34.88
Age	20–25	120	27.91
	26–30	110	25.58
	31–35	78	18.14
	36–40	56	13.02
	Above 41	64	15.35
Educational Level	Diploma/Certificates	100	23.26
	Higher National Degree	170	39.53
	Bachelor’s Degree	86	20.00
	Masters/PGD	72	16.82
Social Media Platforms	Facebook	67	15.58
	Twitter	93	21.63
	WhatsApp	149	34.65
	Others	119	27.80
Tourism destination regions	Greater Accra	138	32.09
	Central Region	114	26.52
	Upper West	48	11.16
	Western Region	83	19.77
	Ashanti region	45	10.46
How often do you use SM	Daily	180	41.86
	Weekly	100	23.26
	Monthly	148	34.58
Social Media Devices	Mobile Device Only	125	29.07
	PC/Computer	105	24.42
	Both	198	46.26
Do you use social media for tourism traveling purposes?	Yes	325	56.98
	No	103*	43.02
Sample Size (n)		428	100

Note.*This figure was deleted before hypothesis testing to get the actual respondents who use social media for tourism purposes.

Source: Author’s field survey September–January 2023.

Table 2. Construct, indicator, loading, VIF, CR, AVE, and CA.

Construct	Indicator	Loading	VIF	CR	AVE	CA
Availability of information	AIT1: Online information shared on destinations by other guests or visitors motivates me to visit	0.838	2.290	0.941	0.798	0.916
	AIT2: Information from other guests or visitors is critical and highly influential in destination choice	0.904	3.241
	AIT3: Obtaining valuable information from other guests or visitors assists in trip planning and destination decisions	0.927	3.980
	AIT4: Recommendations from other guests or visitors serve as a source to make destination choices.	0.903	3.231
Destination Image	DI1: Social media promotion helps to conceive a positive image of a destination	0.863	2.413	0.921	0.744	0.885
	DI2: Adequate information about current culture, leisure, amenities, quality service, and community engagement positively affects one’s image of a destination.	0.905	3.012
	DI3: Tourism destination with a good reputation influences my destination choice	0.883	2.812
	DI4: Web designs, videos, and other images posted online form a positive image of a particular destination.	0.797	1.756
Behavioral Goals	BG1: Information shared on social media is having a strong impact on my intentions to decide.	0.888	3.259	0.927	0.718	0.902
	BG2: Destination image and perceived value directly affect tourist Behavioural intentions	0.838	3.045
	BG3: Experienced posts and videos from tourists on social media platforms influence tourist behavioral goals	0.777	2.220
	BG4: The attitude of tourism service providers in executing services influences tourists’ intention to visit the destination.	0.862	2.970
	BG5: Quality service, destination image, and satisfaction have a strong impact on Behavioural goals	0.867	2.931
Social Media	SM1: social media provides tourism-related information to potential tourists.	0.886	2.816	0.947	0.816	0.925
	SM2: Social media aids tourists in the information search process and facilitates travel	0.899	3.088
	SM3: social media helps in conveying new tourism destination information	0.921	3.680
	SM4: social media facilitates customer service	0.907	3.186
Tourism Contentment	TC1: Tourist satisfaction is essential in making destination decisions	0.883	2.600	0.947	0.812	0.823
	TC2: Satisfied tourists are likely to recommend to others through social media platforms	0.902	3.361
	TC3: Information provided by tourist service providers online is satisfied by potential tourists.	0.923	3.996
	TC4: Tourism quality services enhance tourist satisfaction	0.896	3.033
Tourism Destination Decisions	TDD1: Information online helps to evaluate different tourism destination	0.797	4.269	0.920	0.744	0.937
	TDD2: In my view, the information provided online is my reliable source of information to make a destination choice.	0.731	4.311
	TDD3: Quality service, community engagement, and tourism destination promotion influence tourist destination decisions.	0.923	4.314
	TDD4: In my view, destination image influences my decision to choose a particular destination	0.977	3.909

Source: Author’s processing from SmartPLS 4.0 software.

Table 3. Discriminant validity-Fornell-Larcker criterion.

Constructs	Available Information	Behavioral Goals	Destination Image	Social Media	Tourism Destination Decision	Tourist Contentment
Available Information	0.893
Behavioral Goals	0.777	0.847
Destination Image	0.873	0.799	0.863
Social Media	0.801	0.751	0.797	0.903
Tourism Destination Decision	0.082	0.034	0.051	0.046	0.863
Tourist Contentment	0.830	0.791	0.811	0.774	0.051	0.901

Note. The diagonal bold values indicate the square root of Average Extracted Variance (AVE).

Source: processing from SmartPLS 4.0 software.

Figure A1. Empirically tested research model.

Table 4. Hypothetical path coefficient.

Constructs	Original Sample	Sample Mean	Standard Deviation	T- Statistics	P Values	Test Outcome
H1: TC -> SM	0.774	0.776	0.038	20.372	0.000	Agreed
H2: DI -> SM	0.797	0.799	0.037	21.758	0.000	Agreed
H3a: BG-> SM	0.751	0.752	0.039	19.309	0.000	Agreed
H3b: BG -> DD	−0.046	−0.018	0.117	0.391	0.696	Not Agreed
H4a: AI -> SM	0.801	0.804	0.042	18.972	0.000	Agreed
H4b: AI -> DD	0.212	0.073	0.194	1.094	0.275	Not Agreed
H5: SM -> DD	−0.013	−0.033	0.120	0.108	0.914	Not Agreed
		R Square		R Square Adjusted
Tourism Destination Decision		0.009		−0.002
Social Media		0.711		0.706

Source: processing from SmartPLS 4.0 software.

Note. Availability of Information (AI), Destination Image (DI), tourist contentment (TC), social media (SM), Destination Decision (DD), and Behavioural Goals (BG).