Acceptance and use of technology by older adults for choosing a tour-ism destination: a study using UTAUT2

Moura, Andréia Cássia de; Gosling, Marlusa de Sevilha; Christino, Juliana Maria Magalhães; Macedo, Sâmara Borges

doi:10.7784/rbtur.v11i2.1277

Acessibilidade / Reportar erro

Brasil

Revista Brasileira de Pesquisa em Turismo

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Artigos • Rev. Bras. Pesq. Tur. 11 (02) • May-Aug 2017 • https://doi.org/10.7784/rbtur.v11i2.1277 copy

Acceptance and use of technology by older adults for choosing a tour-ism destination: a study using UTAUT2

Aceptación y uso de la tecnología para la elección de destinos turísticos por personas de la tercera edad: un estudio con UTAUT2

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Older adults are increasingly interested in new technologies and relate them to learning, social inclusion, and leisure. Considering the high number of changes in the profile of the Brazilian elderly and the tourism and technological contexts, this work aims to understand the behavioral intentions and the use of the Internet by the elderly for choosing a tourism destination. To this end, the work extended the UTAUT2 Model of Venkatesh, Thong and Xu (2012), including new constructs related to technology: Perceived Risk and Trust, by Slade et al. (2015) and adding Attitude, based on Curras-Perez, Ruiz-Mafe and Sanz-Blas (2014). The study is characterized as exploratory-descriptive. A survey was conducted online and face-to-face, for two months. Statistical analysis of multivariate analysis was performed using SPSS20 and the modeling analysis of structural equations using SmartPLS. The sample obtained was of 211 older adults who use Internet for tourism purposes. As a result, the relations of the Habit, Hedonic Motivation, Trust, and Performance Expectancy as determinants of the Internet Use Attitude for tourism purposes and, in addition to that, the relation of the Habit construct, positively affecting the Use Behavior. As far as the originality of the work is concerned, Attitude was a new concept used to compose the model, bringing something unprecedented to this field of studies in Brazil. In addition, the innovations include the application of the UTAUT2 model to the Brazilian context, in a segment and market sector not yet explored in this field of research - older people and tourism.

Keywords:
Elderly; Tourism Destinations; Internet; Technology; Unified Theory of Acceptance and Use of Technology 2 (UTAUT2).

Characteristics	Type	Quantity	Percentage
Age	Between 60 and 70	166	78.7
	Between 71 and 80	38	18.0
	More than 81	7	3.3
Gender	Female	147	69.7
	Male	61	28.9
	Missing data	3	1.4
Education	Incomplete primary education	3	1.4
	Complete primary education	2	.9
	Incomplete secondary education	5	2.4
	Complete secondary education	38	18.0
	Incomplete tertiary education	18	8.5
	Complete tertiary education	91	43.1
	Postgraduate education	52	24.6
	Missing data	2	0.9
Gross Family Income	Up to R$1,620	10	4.7
	From R$1,620.01 to R$3,240	20	9.5
	From R$3,240.01 to R$5,760	52	24.6
	From R$5,760.01 to R$ 8,280	51	24.2
	More than R$ 8,280.01	73	34.6
	Missing data	5	2.4
Marital Status	Single	18	8.5
	Married	109	51.7
	Divorced	33	15.6
	Widowed	43	20.4
	Other	5	2.4
	Missing data	3	1.4
	TOTAL	211

Associação Nacional de Pesquisa e Pós-Graduação em Turismo Rua Silveira Martins, 115 - cj. 71, Centro, Cep: 01019-000, Tel: 11 3105-5370 - São Paulo - SP - Brazil
E-mail: edrbtur@gmail.com

Acompanhe os números deste periódico no seu leitor de RSS

[1] Andréia Cássia de Moura

PhD student in Business Administration in the Postgraduate Program in Business Administration from the Federal University of Minas Gerais - UFMG. Master's degree in Business Administration from UFMG, Specialist in Strategic Business from UFMG and Bachelor's degree in Business Administration from UFMG. Email: andreia.moura@estacio.br

Items of the questionnaire	Author
Considering the objective of choosing tourism destinations, classify your degree of agreement with the following statements:
ED1. The Internet is useful in my daily life for this purpose.
ED2. Using the Internet increases my chances of achieving things that are important to me for that purpose.
ED3. Using the Internet helps me get things done faster for that purpose.
ED4. Using the Internet makes my search for that purpose more efficient.
EE1. I learn easily how to use the Internet for that purpose.
EE2. Interacting with the Internet for that purpose is clear and understandable.
EE3. The Internet is easy to use for that purpose.
ED4. It is easy for me to become more skilled at using the Internet for that purpose.
IS1. People who are important to me think that I should use the Internet for that purpose.
IS2. People who have a lot of fun with me think that I should use the Internet for that purpose.	Venkatesh, Thong and Xu (2012Venkatesh, V, Thong, J. L. & Xu, X. (2012). Consumer acceptance and use of information Technology: extending the unified theory of acceptance and use of technology. MIS Quarterly . 36(1), pp. 157-178.)
IS3. The people whose opinions I value prefer that I use the Internet for that purpose.
FC1. I have the necessary resources to use the Internet for that purpose.
FC2. I have the knowledge to use the Internet for that purpose.
FC3. The Internet is compatible with other technologies that I use for that purpose.
FC4. I can get help from others when I have difficulties using the Internet for that purpose.
HM1. Using the Internet for that purpose is fun.
HM2. Using the Internet for that purpose is agreeable.
HT1. The use of the Internet for that purpose has become a habit for me.
HT2. I am addicted to using the Internet for that purpose.
HT3. I must use the Internet for that purpose.
HT4. Using the Internet for that purpose has become natural to me.
CF1. I believe that the information obtained on the Internet for that purpose is reliable.	Slade et al. (2015Slade, E. L., Dwivedi, Y. K., Piercy, N. C. & Williams, M. D. (2015). Modeling Consumers Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology & Marketing, 32(8), pp. 860-873.)
CF2. I believe the Internet is safe for that purpose.
CF3. I believe that the information on the Internet is reliable for that purpose.
CF4. I rely on information and transactions made through the Internet for that purpose.
RP1. I feel insecure by providing personal information on the Internet for this purpose.	Slade et al. (2015Slade, E. L., Dwivedi, Y. K., Piercy, N. C. & Williams, M. D. (2015). Modeling Consumers Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology & Marketing, 32(8), pp. 860-873.)
RP2.I worry about using the Internet for that purpose because other people may be able to access my account.
RP3. I feel insecure sending sensitive information through the Internet.
AT1. It is fun to access the Internet for tourism purposes.	Curras-Perez, Ruiz-Mafe and Sanz-Blas, (2014Curras-Perez, R., Ruiz-Mafe, C. & Sanz-Blas, S. (2014). Determinants of user behaviour and recommendation in social networks: an integrative approach from the uses and gratifications perspective. Industrial Management & Data Systems, 114(9), pp. 1477-1498.)
AT2. I think it is a good idea to use the Internet for this purpose.
AT3. It is pleasant to connect the Internet to that purpose.
AT4. I think the idea of using the Internet for tourism purposes is positive.
AT5. I like to use the Internet for tourism purposes.
IC1. I intend to continue to use the Internet for that purpose in the future.	Venkatesh, Thong and Xu (2012Venkatesh, V, Thong, J. L. & Xu, X. (2012). Consumer acceptance and use of information Technology: extending the unified theory of acceptance and use of technology. MIS Quarterly . 36(1), pp. 157-178.)
IC2. I will always try to use the Internet for that purpose daily.
IC3. I plan to continue using the Internet for that purpose frequently.
CU1 A). Search engines (e.g. Google) for tourism.
CU2 B) Specific search sites (e.g. city hotel, decolar.com, booking).
CU3 C) WhatsApp for tourism.
CU4 D) Social Network (e.g. Instagram, Facebook) aimed at tourism.

	Components
	1	2	3	4	5	6	7	Comunal.
ED1			0.638	0.330				0.653
ED2			0.815					0.838
ED3			0.803					0.813
ED4	0.307		0.733					0.705
EE1	0.812							0.767
EE2	0.728							0.711
EE3	0.792							0.758
EE4	0.734				0.311			0.741
IS1					0.849			0.851
IS2					0.883			0.886
IS3					0.723			0.671
MH1						0.799		0.820
MH2						0.834		0.850
MH3						0.850		0.823
HT1	0.306			0.689				0.777
HT2				0.781				0.739
HT3				0.789				0.790
HT4	0.347			0.612		0.337		0.730
CO1		0.797						0.761
CO2		0.874						0.858
CO3		0.882						0.842
CO4		0.865						0.818
RP1							0.752	0.644
RP2							0.869	0.766
RP3							0.903	0.821
CF1	0.448		0.413					0.473
CF2	0.745			0.324				0.731
CF3	0.440		0.347	0.311				0.473
CF4	0.380							0.297

	Component
	1	2	Comunal.
AT1	0.841		0.716
AT2	0.890		0.806
AT3	0.838		0.715
AT4	0.864		0.756
AT5	0.859		0.807
IC1	0.756		0.624
IC2	0.531	0.428	0.465
IC3	0.566	0.448	0.520
CU1_A		0.677	0.522
CU2_B		0.731	0.624
CU3_C		0.781	0.613
CU4_D		0.782	0.612

Constructs	Indicators	Outer Loadings	AVE	Cronbach's alpha	CR
Attitude	AT1	0.881	0.789	0.933	0.949
	AT2	0.909
	AT3	0.877
	AT4	0.868
	AT5	0.903
Trust	CO1	0.877	0.814	0.924	0.946
	CO2	0.936
	CO3	0.905
	CO4	0.889
Use behavior	CU1_A	0.797	0.592	0.775	0.852
	CU2_B	0.827
	CU3_C	0.719
	CU4_D	0.724
Performance Expectancy	ED1	0.833	0.735	0.880	0.917
	ED2	0.911
	ED3	0.877
	ED4	0.802
Effort Expectancy	EE1	0.845	0.758	0.894	0.926
	EE2	0.885
	EE3	0.888
	EE4	0.863
Habit	HT1	0.885	0.743	0.885	0.920
	HT2	0.824
	HT3	0.870
	HT4	0.867
Social Influence	IS1	0.920	0.809	0.881	0.927
	IS2	0.941
	IS3	0.832
Hedonic Motivation	MH1	0.913	0.825	0.894	0.933
	MH2	0.922
	MH3	0.888
Perceived Risk	RP1	0.686	0.553	0.818	0.701
	RP2	0.643
	RP3	0.667

	AT	CO	CU	ED	EE	HT	IS	MH	RP
AT	0.888
CO	0.467	0.902
CU	0.395	0.295	0.770
ED	0.508	0.395	0.420	0.857
EE	0.489	0.379	0.436	0.576	0.871
HT	0.628	0.486	0.579	0.574	0.555	0.862
IS	0.331	0.319	0.407	0.508	0.376	0.487	0.900
MH	0.566	0.301	0.371	0.464	0.474	0.543	0.393	0.908
RP	0.047	0.187	0.036	0.121	-0.073	0.056	0.174	0.073	0.560

	Original Sample	Sample Average	SD	Statistics T	P value
AT -> CU	0.052	0.056	0.066	0.799	0.424
CO -> AT	0.182	0.180	0.067	2.723	0.006
CO -> RP	0.187	0.056	0.180	1.035	0.301
ED -> AT	0.128	0.125	0.063	2.026	0.043
EE -> AT	0.065	0.070	0.072	0.905	0.366
HT -> AT	0.316	0.311	0.076	4.176	0.000
HT -> CU	0.546	0.548	0.063	8.678	0.000
IS -> AT	-0.077	-0.074	0.066	1.160	0.246
MH -> AT	0.282	0.286	0.073	3.870	0.000
RP -> AT	-0.022	-0.005	0.056	0.393	0.695

Hypothesis	Code	Result	Analysis
AT -> IC	H11	Rejected	Factor analysis pointed to the exclusion of IC construct.
CF -> CU	H6b	Rejected	Factor analysis pointed to the exclusion of CF construct.
CF -> AT	H6a	Rejected	Factor analysis pointed to the exclusion of CF construct.
CO -> AT	H9	Supported	The significance of the relationship between Trust (CO) and Attitude (AT) constructs was satisfactory, and it can be said that Trust is a predictor of Attitude in this study.
ED -> AT	H2	Supported	The significance of the relationship between Performance Expectancy (ED) and Attitude (AT) constructs was satisfactory, and it can be said that Performance Expectancy is a predictor of Attitude in this study.
EE -> AT	H1	Rejected	The significance of the relationship between Effort Expectancy (EE) and Attitude (AT) constructs was not satisfactory, and it can be said that Effort Expectancy is not a predictor of Attitude in this study.
HT -> CU	H5b	Supported	The significance of the relationship between Habit (HT) and Use Behavior (CU) constructs was satisfactory, and it can be said that Habit is a predictor of Use Behavior.
HT -> AT	H5a	Supported	The significance of the relationship between Habit (HT) and Attitude (AT) constructs was satisfactory, and it can be said that Habit is a predictor of Attitude.
IC -> CU	H7	Rejected	Factor analysis pointed to the exclusion of IC construct.
IS -> AT	H3	Rejected	The significance of the relationship between Social Influence (IS) and Attitude (AT) was not satisfactory, and it can be said that Social Influence is not a predictor of Attitude in this study.
MH -> AT	H4	Supported	The significance of the relationship between Hedonic Motivation (MH) and Attitude (AT) constructs was satisfactory, and it can be said that Hedonic Motivation is a predictor of Attitude.
RP -> AT	H8	Rejected	The significance of the relationship between Perceived Risk (PR) and Attitude (AT) constructs was not satisfactory, and it can be said that Perceived Risk is not a predictor of Attitude in this study.
CO -> RP	H10	Rejected	The significance of the relationship between Trust (CO) and Perceived Risk (RP) constructs was not satisfactory, and it can be said that Trust does not negatively affect Perceived Risk in this study.
AT -> CU		Rejected	Hypothesis created from the exclusion of the IC construct, leaving a direct relationship between Attitude (AT) and Use Behavior (CU). However, it was rejected.

	Original Sample	Sample Average	SD	Statistics T	P Value
AT	0.513	0.535	0.056	9.239	0.000
CU	0.337	0.346	0.049	6.851	0.000
RP	0.035	0.036	0.025	1.407	0.160