Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps

Christino, Juliana M. M.; Cardozo, Érico Aurélio Abreu; Petrin, Renata; Pinto, Lais H. de Aguiar

doi:10.7819/rbgn.v23i1.4095

Juliana M. M. Christino

.Federal University of Minas Gerais, Faculty of Economic Sciences, Center for Graduate Studies and Research in Administration - CEPEAD/UFMG, Belo Horizonte, Brazil

https://orcid.org/0000-0003-0186-9704

Érico Aurélio Abreu Cardozo

.Federal University of Minas Gerais, Faculty of Economic Sciences, Center for Graduate Studies and Research in Administration - CEPEAD/UFMG, Belo Horizonte, Brazil

https://orcid.org/0000-0002-5100-5464

Renata Petrin

.Federal University of Minas Gerais, Faculty of Economic Sciences, Center for Graduate Studies and Research in Administration - CEPEAD/UFMG, Belo Horizonte, Brazil

https://orcid.org/0000-0001-5416-9205

Lais H. de Aguiar Pinto

.Federal University of Minas Gerais, Faculty of Economic Sciences, Belo Horizonte, Brazil

https://orcid.org/0000-0003-4306-1359

Responsible Editor:

Prof. Dr. Sebastián Mollino

Reviewers:

Iviane Ramos de Luna; Ramayah Thursamy; Francisco Javier Montoro-Ríos.

Conflicts of interest:

The authors have no conflict of interest to declare

1
. Juliana Maria Magalhães Christino, PhD in Administration, Federal University of Minas Gerais - UFMG, Minas Gerais, Brazil. E-mail: julianammc@face.ufmg.br

2
. Érico Aurélio Abreu Cardozo, Master in Business Administration, Federal University of Espírito Santo - UFES, Espirito Santo, Brazil. E-mail: erico.cardozo@gmail.com

3
. Renata Petrin, Master in Administration, Pontifical Catholic University of Minas Gerais, Minas Gerais, Brazil. E-mail: renata_petrin@yahoo.com.br

4
. Lais Harsányi de Aguiar Pinto, Bachelor in Administration, Federal University of Minas Gerais - UFMG, Minas Gerais, Brazil. E-mail: laisharsanyi@gmail.com

1
. Juliana Maria Magalhães Christino: definition of research problem; Development of hypotheses or research questions (empirical studies). Theoretical foundation/ Literature; Data collection Review; Critical revision of the manuscript. Manuscript Writing;

2
. Érico Aurélio Abreu Cardozo: Development of hypotheses or research questions (empirical studies); Definition of methodological procedures; Data collection; Statistical analysis; Analysis and interpretation of data; Critical revision of the manuscript.

3
. Renata Petrin: Theoretical foundation/ Literature review; Manuscript Writing;

4
. Lais Harsányi de Aguiar Pinto: Data collection; Manuscript Writing;

Figures (2)
Tables (7)

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Figure 1
Research Model and Hypotheses

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Figure 2
Structural Model Result

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Table 1
Sample description

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Table 2
Convergent validity and reliability and internal consistency

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Table 3
Fornell-Larcker Criterion

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Table 4
Heterotrait - Monotrait Ratio (HTMT) Criterion

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Table 5
Path coefficients between the constructs and their levels of significance

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Construct Items Source Performance expectation PE1 I find it useful to use delivery applications for restaurants. Venkatesh, et al. (2012) PE2 Using delivery applications for restaurants increases my options. PE3 Using delivery applications for restaurants allows me to eat what I like more easily. *PE4 Using delivery applications for restaurants allows me to choose meals more quickly. Expected effort EE1 Learning how to use delivery applications for restaurants is easy. Venkatesh, et. al. (2012) EE2 Interacting with restaurant delivery applications is simple and easy to understand. EE3 I find it easy to use restaurant delivery applications. EE4 It’s easy for me to become skilled in using restaurant delivery applications. Social influence SI1 Important people for me think that I should use restaurant delivery applications. Venkatesh, et. al. (2012) SI2 People I relate to think I should use restaurant delivery apps. SI3 People whose opinions I value prefer me to use restaurant delivery apps. Facilitating conditions *FC1 I have the resources (smartphone, internet access, payment methods) to use restaurant delivery apps. Venkatesh, et al. (2012) FC2 I have the necessary knowledge to use restaurant delivery apps. FC3 The way I use restaurant delivery apps is similar to other platforms that I use on my phone. *FC4 I can get help from others when I have difficulties using the restaurant delivery applications. Hedonic motivations HM1 Using restaurant delivery apps is fun. Venkatesh, et al. (2012) HM2 Using restaurant delivery apps is nice. HM3 Using restaurant delivery apps is very interesting. Price value PV1 Restaurant delivery apps are reasonably priced. Venkatesh, et al. (2012) PV2 The delivery cost of restaurant delivery applications is very cost-effective. PV3 At current delivery rates, restaurant delivery applications offer good value. Habit HA1 The use of restaurant delivery applications has become a habit for me. Venkatesh, et al. (2012) HA2 I am addicted to using restaurant delivery applications. HA3 I need to use restaurant delivery applications. HA4 Using restaurant delivery apps has become natural for me. Behavioral intention BI1 I intend to continue using restaurant delivery applications in the future. Venkatesh, et al. (2012) BI2 I will always try to use restaurant delivery apps when I want to order food at home. BI3 I plan on continuing to use delivery applications for restaurants frequently. Susceptibility to offers SO1 Redeeming coupons and/or taking advantage of promotional offers on restaurant delivery apps makes me feel good. Feng (2017) *SO2 I am more biased towards buying or becoming a customer of restaurant delivery apps that offer promotions. SO3 Aside from the money I save, redeeming coupons and taking advantage of promotional offers on restaurant delivery apps makes me very happy. Innovativeness IN1 If I hear about new technology, I try it. Tak and Panwar (2017) IN2 Within my social circle, I’m usually the first to try out new technologies. IN3 I like to try out new technologies. *IN4 In general, I am hesitant to try new technologies. Convenience CO1 I prefer the application I use because it’s the easiest to manipulate. Experts CO2 I prefer the app I use because delivery is quicker. *CO3 I prefer the app I use because it is the only one with my favorite restaurant(s). CO4 I prefer the app I use because it offers the best promotions. *CO5 I prefer the app I use because delivery is cheaper. CO6 I prefer the app I use because it has the best coverage. CO7 I prefer the app I use because it offers the best customer support. Usage behavior USB Once a month (1). C. Martins, et al. (2014) Once a week (2). Once every 2 or 3 days (3). Every day (4). Several times a day (5). Note: *The respective indicator was excluded because it does not present statistical significance and relevance.

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Variable N. % Variable N. % Male Gender Gender Female Once a month (1). 14 8.9% Once a month (1). 9 4.8% Once a week (2). 37 23.4% Once a week (2). 43 23.1% Once every 2 or 3 days (3). 43 27.2% Once every 2 or 3 days (3). 57 30.6% Every day (4). 52 32.9% Every day (4). 60 32.3% Several times a day (5). 12 7.6% Several times a day (5). 17 9.1% Age group - 18 to 23 years old Age group - 24 to 29 years old Once a month (1). 10 7.9% Once a month (1). 3 2.1% Once a week (2). 8 6.3% Once a week (2). 15 10.6% Once every 2 or 3 days (3). 55 43.3% Once every 2 or 3 days (3). 54 38.3% Every day (4). 41 32.3% Every day (4). 64 45.4% Several times a day (5). 13 10.2% Several times a day (5). 5 3.5% Age group - 30 to 35 years old Age group - 36 to 41 years old Once a month (1). 2 5.7% Once a month (1). 2 10.0% Once a week (2). 9 25.7% Once a week (2). 8 40.0% Once every 2 or 3 days (3). 16 45.7% Once every 2 or 3 days (3). 6 30.0% Every day (4). 6 17.1% Every day (4). 4 20.0% Several times a day (5). 2 5.7% Several times a day (5). 0 0.0% Age group - 42 to 47 years old Age group - 48 to 53 years old Once a month (1). 2 28.6% Once a month (1). 1 20.0% Once a week (2). 3 42.9% Once a week (2). 2 40.0% Once every 2 or 3 days (3). 1 14.3% Once every 2 or 3 days (3). 1 20.0% Every day (4). 1 14.3% Every day (4). 1 20.0% Several times a day (5). 0 0.0% Several times a day (5). 0 0.0% Age group - 54 to 59 years old Age group - > 60 years Once a month (1). 2 28.6% Once a month (1). 1 50.0% Once a week (2). 3 42.9% Once a week (2). 1 50.0% Once every 2 or 3 days (3). 2 28.6% Once every 2 or 3 days (3). 0 0.0% Every day (4). 0 0.0% Every day (4). 0 0.0% Several times a day (5). 0 0.0% Several times a day (5). 0 0.0% Marital status - Married Marital Status - Divorced Once a month (1). 2 3.3% Once a month (1). 1 14.3% Once a week (2). 13 21.3% Once a week (2). 2 28.6% Once every 2 or 3 days (3). 19 31.1% Once every 2 or 3 days (3). 3 42.9% Every day (4). 25 41.0% Every day (4). 1 14.3% Several times a day (5). 2 3.3% Several times a day (5). 0 0.0% Civil Status - Separated Marital status - Single Once a month (1). 0 0.0% Once a month (1). 18 6.6% Once a week (2). 0 0.0% Once a week (2). 107 39.2% Once every 2 or 3 days (3). 2 100.0% Once every 2 or 3 days (3). 61 22.3% Every day (4). 0 0.0% Every day (4). 48 17.6% Several times a day (5). 0 0.0% Several times a day (5). 29 10.6% Marital status - Widow(er) Family income - up to R$1.874.00 Once a month (1). 1 100.0% Once a month (1). 2 7.1% Once a week (2). 0 0.0% Once a week (2). 6 21.4% Once every 2 or 3 days (3). 0 0.0% Once every 2 or 3 days (3). 15 53.6% Every day (4). 0 0.0% Every day (4). 3 10.7% Several times a day (5). 0 0.0% Several times a day (5). 2 7.1% Family income - R$1,874.01 to R$3,748.00 Family income - R$18,740.01 or more Once a month (1). 2 3.6% Once a month (1). 3 4.8% Once a week (2). 11 20.0% Once a week (2). 9 14.5% Once every 2 or 3 days (3). 16 29.1% Once every 2 or 3 days (3). 19 30.6% Every day (4). 20 36.4% Every day (4). 27 43.5% Several times a day (5). 6 10.9% Several times a day (5). 4 6.5% Family income - R$3,748.01 to R$9,370.00 Family income - R$9,370.01 to R$18,740.00 Once a month (1). 15 11.5% Once a month (1). 6 8.7% Once a week (2). 11 8.5% Once a week (2). 18 26.1% Once every 2 or 3 days (3). 58 44.6% Once every 2 or 3 days (3). 31 44.9% Every day (4). 43 33.1% Every day (4). 13 18.8% Several times a day (5) 3 2.3% Several times a day (5). 1 1.4%

Variable	N.	%	Variable	N.	%
Gender			Marital status
Male	158	45.9%	Married	61	17.7%
Female	186	54.1%	Divorced	7	2.0%
Age group			Separated	2	0,6%
18 to 23 years	127	36.9%	Single	273	79.4%
24 to 29 years	141	41.0%	Widower	1	0.3%
30 to 35 years	35	10.2%	Family income
36 to 41 years	20	5.8%	R$1,874.00	28	8,1%
42 to 47 years	7	2.0%	R$1,874.01 to R$3,748.00	55	16.0%
48 to 53 years	5	1.5%	R$18,740.01 or more	62	18.0%
54 to 59 years	7	2.0%	R$3,748.01 to R$9,370.00	130	37.8%
> 60 years	2	0.6%	R$9,370.01 to R$18,740.00	69	20.1%
∑	344	100%	∑	344	100%

Construct	Cronbach’s alpha	Composite reliability	Average variance extracted	Item	Loading	Standard deviation	T Statistics
Convenience	0.778	0.846	0.523	CO1	0.747	0.046	19.079
				CO2	0.728	0.073	10.471
				CO4	0.701	0.028	29.846
				CO6	0.723	0.032	25.653
				CO7	0.738	0.025	34.163
Facilitating conditions	0.700	0.804	0.673	FC2	0.871	0.034	24.150
				FC3	0.767	0.037	20.494
Expected effort	0.857	0.903	0.700	EE1	0.850	0.056	12.426
				EE2	0.814	0.044	17.193
				EE3	0.867	0.057	10.890
				EE4	0.814	0.011	79.919
Performance Expectation	0.723	0.804	0.578	PE1	0.804	0.021	39.055
				PE2	0.723	0.021	39.110
				PE3	0.752	0.014	59.708
Habit	0.875	0.912	0.722	HA1	0.896	0.017	52.186
				HA2	0.817	0.028	28.994
				HA3	0.822	0.011	82.367
				HA4	0.863	0.012	74.032
Behavioral intention	0.833	0.900	0.749	BI1	0.870	0.024	34.758
				BI2	0.818	0.018	49.791
				BI3	0.906	0.021	43.335
Innovativeness	0.868	0.918	0.789	IN1	0.918	0.009	101.720
				IN2	0.848	0.015	59.873
				IN3	0.897	0.029	29.377
Social influence	0.899	0.937	0.832	SI1	0.892	0.014	65.877
				SI2	0.939	0.028	29.846
				SI3	0.904	0.165	5.893
Hedonic motivations	0.814	0.888	0.726	HM1	0.840	0.217	3.546
				HM2	0.893	0.990	2.333
				HM3	0.821	0.044	20.521
Susceptibility to offers	0.755	0.869	0.771	SO1	0.974	0.035	26.841
				SO3	0.770	0.025	38.367
Usage behavior	NA	NA	NA	USB	1.000	0.000
Price value	0.818	0.947	0.857	PV1	0.905	0.846	21.455
				PV2	0.931	0.768	10.298
				PV3	0.941	0.876	112.772

Construct	USB	FC	PE	EE	HA	SI	IN	BI	HM	CO	SO	PV
USB	1.000
FC	0.004	0.820
PE	-0.031	0.305	0.760
EE	-0.074	0.586	0.343	0.837
HA	0.037	0.287	0.425	0.344	0.850
SI	0.109	0.221	0.428	0.163	0.395	0.912
IN	0.063	0.234	0.201	0.241	0.415	0.208	0.888
BI	-0.041	0.364	0.514	0.392	0.714	0.330	0.307	0.866
HM	-0.058	0.271	0.502	0.347	0.430	0.375	0.276	0.418	0.852
CO	0.018	0.160	0.300	0.198	0.344	0.281	0.345	0.263	0.358	0.723
SO	0.106	0.212	0.291	0.199	0.304	0.279	0.374	0.276	0.320	0.323	0.878
PV	0.038	0.063	0.064	0.067	0.195	0.220	0.123	0.160	0.229	0.211	0.057	0.926

Construct	USB	FC	PE	EE	HA	SI	IN	BI	HM	CO	SO	PV
USB	-
FC	0.014	-
PE	0.038	0.528	-
EE	0.079	0.864	0.454	-
HA	0.040	0.391	0.549	0.376	-
SI	0.116	0.327	0.555	0.188	0.452	-
IN	0.072	0.353	0.266	0.275	0.467	0.230	-
BI	0.044	0.548	0.673	0.463	0.800	0.379	0.358	-
HM	0.066	0.424	0.691	0.400	0.515	0.439	0.325	0.494	-
CO	0.031	0.239	0.406	0.237	0.423	0.330	0.401	0.306	0.458	-
SO	0.102	0.378	0.396	0.267	0.363	0.322	0.467	0.336	0.392	0.430	-
PV	0.039	0.095	0.085	0.087	0.231	0.241	0.143	0.182	0.278	0.263	0.072	-

	Path	β	Standard deviation	T Statistics	P Value	Level of Significance	Result
H1	Intention to use -> Usage behavior	0.152	0.073	2.075	0.038	**	Supported
H2	Innovativeness -> Intention to use	0.009	0.045	2.236	0.025	**	Supported
H3	Susceptibility to offers -> Usage behavior	0.114	0.063	1.999	0.072	***	Supported
H4	Convenience -> Intention to use	0.036	0.04	2.070	0.039	**	Supported
H5	Performance expectation -> Intended Use	0.229	0.05	4.562	0.000	*	Supported
H6	Expected effort -> Intention to use	0.059	0.052	2.547	0.011	**	Supported
H7	Social influence -> Intention to use	-0.034	0.049	0.702	0.482	NS	Not Supported
H8	Price value -> Intention to use	0.032	0.039	2.400	0.016	**	Supported
H9	Hedonic motivations -> Intention to use	0.027	0.048	0.572	0.567	NS	Not Supported
H10	Facilitating conditions -> Intention to use	0.099	0.048	2.047	0.041	**	Supported
H11	Facilitating conditions -> Usage behavior	0.004	0.059	0.067	0.946	NS	Not Supported
H12	Habit -> Intention to use	0.580	0.044	13.095	0.000	*	Supported
H13	Habit -> Usage behavior	0.110	0.076	2.158	0.031	**	Supported

Construct	Items		Source
Performance expectation	PE1	I find it useful to use delivery applications for restaurants.	Venkatesh, et al. (2012)
	PE2	Using delivery applications for restaurants increases my options.
	PE3	Using delivery applications for restaurants allows me to eat what I like more easily.
	*PE4	Using delivery applications for restaurants allows me to choose meals more quickly.
Expected effort	EE1	Learning how to use delivery applications for restaurants is easy.	Venkatesh, et. al. (2012)
	EE2	Interacting with restaurant delivery applications is simple and easy to understand.
	EE3	I find it easy to use restaurant delivery applications.
	EE4	It’s easy for me to become skilled in using restaurant delivery applications.
Social influence	SI1	Important people for me think that I should use restaurant delivery applications.	Venkatesh, et. al. (2012)
	SI2	People I relate to think I should use restaurant delivery apps.
	SI3	People whose opinions I value prefer me to use restaurant delivery apps.
Facilitating conditions	*FC1	I have the resources (smartphone, internet access, payment methods) to use restaurant delivery apps.	Venkatesh, et al. (2012)
	FC2	I have the necessary knowledge to use restaurant delivery apps.
	FC3	The way I use restaurant delivery apps is similar to other platforms that I use on my phone.
	*FC4	I can get help from others when I have difficulties using the restaurant delivery applications.
Hedonic motivations	HM1	Using restaurant delivery apps is fun.	Venkatesh, et al. (2012)
	HM2	Using restaurant delivery apps is nice.
	HM3	Using restaurant delivery apps is very interesting.
Price value	PV1	Restaurant delivery apps are reasonably priced.	Venkatesh, et al. (2012)
	PV2	The delivery cost of restaurant delivery applications is very cost-effective.
	PV3	At current delivery rates, restaurant delivery applications offer good value.
Habit	HA1	The use of restaurant delivery applications has become a habit for me.	Venkatesh, et al. (2012)
	HA2	I am addicted to using restaurant delivery applications.
	HA3	I need to use restaurant delivery applications.
	HA4	Using restaurant delivery apps has become natural for me.
Behavioral intention	BI1	I intend to continue using restaurant delivery applications in the future.	Venkatesh, et al. (2012)
	BI2	I will always try to use restaurant delivery apps when I want to order food at home.
	BI3	I plan on continuing to use delivery applications for restaurants frequently.
Susceptibility to offers	SO1	Redeeming coupons and/or taking advantage of promotional offers on restaurant delivery apps makes me feel good.	Feng (2017)
	*SO2	I am more biased towards buying or becoming a customer of restaurant delivery apps that offer promotions.
	SO3	Aside from the money I save, redeeming coupons and taking advantage of promotional offers on restaurant delivery apps makes me very happy.
Innovativeness	IN1	If I hear about new technology, I try it.	Tak and Panwar (2017)
	IN2	Within my social circle, I’m usually the first to try out new technologies.
	IN3	I like to try out new technologies.
	*IN4	In general, I am hesitant to try new technologies.
Convenience	CO1	I prefer the application I use because it’s the easiest to manipulate.	Experts
	CO2	I prefer the app I use because delivery is quicker.
	*CO3	I prefer the app I use because it is the only one with my favorite restaurant(s).
	CO4	I prefer the app I use because it offers the best promotions.
	*CO5	I prefer the app I use because delivery is cheaper.
	CO6	I prefer the app I use because it has the best coverage.
	CO7	I prefer the app I use because it offers the best customer support.
Usage behavior	USB	Once a month (1).	C. Martins, et al. (2014)
		Once a week (2).
		Once every 2 or 3 days (3).
		Every day (4).
		Several times a day (5).

Variable	N.	%	Variable	N.	%
Male Gender			Gender Female
Once a month (1).	14	8.9%	Once a month (1).	9	4.8%
Once a week (2).	37	23.4%	Once a week (2).	43	23.1%
Once every 2 or 3 days (3).	43	27.2%	Once every 2 or 3 days (3).	57	30.6%
Every day (4).	52	32.9%	Every day (4).	60	32.3%
Several times a day (5).	12	7.6%	Several times a day (5).	17	9.1%
Age group - 18 to 23 years old			Age group - 24 to 29 years old
Once a month (1).	10	7.9%	Once a month (1).	3	2.1%
Once a week (2).	8	6.3%	Once a week (2).	15	10.6%
Once every 2 or 3 days (3).	55	43.3%	Once every 2 or 3 days (3).	54	38.3%
Every day (4).	41	32.3%	Every day (4).	64	45.4%
Several times a day (5).	13	10.2%	Several times a day (5).	5	3.5%
Age group - 30 to 35 years old			Age group - 36 to 41 years old
Once a month (1).	2	5.7%	Once a month (1).	2	10.0%
Once a week (2).	9	25.7%	Once a week (2).	8	40.0%
Once every 2 or 3 days (3).	16	45.7%	Once every 2 or 3 days (3).	6	30.0%
Every day (4).	6	17.1%	Every day (4).	4	20.0%
Several times a day (5).	2	5.7%	Several times a day (5).	0	0.0%
Age group - 42 to 47 years old			Age group - 48 to 53 years old
Once a month (1).	2	28.6%	Once a month (1).	1	20.0%
Once a week (2).	3	42.9%	Once a week (2).	2	40.0%
Once every 2 or 3 days (3).	1	14.3%	Once every 2 or 3 days (3).	1	20.0%
Every day (4).	1	14.3%	Every day (4).	1	20.0%
Several times a day (5).	0	0.0%	Several times a day (5).	0	0.0%
Age group - 54 to 59 years old			Age group - > 60 years
Once a month (1).	2	28.6%	Once a month (1).	1	50.0%
Once a week (2).	3	42.9%	Once a week (2).	1	50.0%
Once every 2 or 3 days (3).	2	28.6%	Once every 2 or 3 days (3).	0	0.0%
Every day (4).	0	0.0%	Every day (4).	0	0.0%
Several times a day (5).	0	0.0%	Several times a day (5).	0	0.0%
Marital status - Married			Marital Status - Divorced
Once a month (1).	2	3.3%	Once a month (1).	1	14.3%
Once a week (2).	13	21.3%	Once a week (2).	2	28.6%
Once every 2 or 3 days (3).	19	31.1%	Once every 2 or 3 days (3).	3	42.9%
Every day (4).	25	41.0%	Every day (4).	1	14.3%
Several times a day (5).	2	3.3%	Several times a day (5).	0	0.0%
Civil Status - Separated			Marital status - Single
Once a month (1).	0	0.0%	Once a month (1).	18	6.6%
Once a week (2).	0	0.0%	Once a week (2).	107	39.2%
Once every 2 or 3 days (3).	2	100.0%	Once every 2 or 3 days (3).	61	22.3%
Every day (4).	0	0.0%	Every day (4).	48	17.6%
Several times a day (5).	0	0.0%	Several times a day (5).	29	10.6%
Marital status - Widow(er)			Family income - up to R$1.874.00
Once a month (1).	1	100.0%	Once a month (1).	2	7.1%
Once a week (2).	0	0.0%	Once a week (2).	6	21.4%
Once every 2 or 3 days (3).	0	0.0%	Once every 2 or 3 days (3).	15	53.6%
Every day (4).	0	0.0%	Every day (4).	3	10.7%
Several times a day (5).	0	0.0%	Several times a day (5).	2	7.1%
Family income - R$1,874.01 to R$3,748.00			Family income - R$18,740.01 or more
Once a month (1).	2	3.6%	Once a month (1).	3	4.8%
Once a week (2).	11	20.0%	Once a week (2).	9	14.5%
Once every 2 or 3 days (3).	16	29.1%	Once every 2 or 3 days (3).	19	30.6%
Every day (4).	20	36.4%	Every day (4).	27	43.5%
Several times a day (5).	6	10.9%	Several times a day (5).	4	6.5%
Family income - R$3,748.01 to R$9,370.00			Family income - R$9,370.01 to R$18,740.00
Once a month (1).	15	11.5%	Once a month (1).	6	8.7%
Once a week (2).	11	8.5%	Once a week (2).	18	26.1%
Once every 2 or 3 days (3).	58	44.6%	Once every 2 or 3 days (3).	31	44.9%
Every day (4).	43	33.1%	Every day (4).	13	18.8%
Several times a day (5)	3	2.3%	Several times a day (5).	1	1.4%

[1] Responsible Editor:

Prof. Dr. Sebastián Mollino

Brasil

Brasil

Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps

Abstract

Purpose:

Design/methodology/approach:

Findings:

Originality/value: