Consumer Attitude and Behavior During Black Friday and Cyber Monday
Pages 147 - 158
Abstract
This study aims to analyze consumer behavior during Cyber Monday and Black Friday in Chile through an information technology acceptance model. An extended technology acceptance model was created to which the Technology Continuance Use Theory was incorporated. The variables used to explain continuance intention (CI) were attitude towards shopping (A), subjective norms (NS), perceived risk (PR), perceived usefulness (PU), shopping enjoyment (SE) and convenience (C). To obtain the data necessary for the structural equation model proposed, a survey was created on the SurveyMonkey platform. The survey was disseminated through social networks during May and June 2019. The results indicated that convenience (C) positively influences shopping enjoyment (SE) (.543). Then, shopping enjoyment is the variable that influences the most attitude (.496), which is directly related, with a standardized regression coefficient of .874, to the purchase continuance intention on Cyber Monday and Black Friday. Consequently, saving time and money by doing online shopping generates a pleasure or enjoyment perception in consumers, which has a positive effect on the perception of making purchases during these events and therefore on the intention to continue buying. Other results, conclusions, and theoretical and practical recommendations are further discussed along the paper.
References
[1]
Ajzen I The theory of planned behaviour Organ. Behav. Hum. Decis. Process. 1991 50 2 179-211
[2]
Arnold MJ and Reynolds KE Hedonic shopping motivations J. Retail. 2003 79 77-95
[3]
Babin BJ, Darden WR, and Griffin M Work and/or fun: measuring hedonic and utilitarian shopping value J. Cons. Res. 1994 20 4 644-656
[4]
Bauer RA Robert SH Consumer behavior as risk taking Dynamic Marketing for a Changing World 1960 Chicago American Marketing Association 389-398
[5]
Black Friday 2018 Chile. https://black-friday.global/es-cl/. Accessed 26 Jan 2021
[6]
Bourlier, A., Gomez, G. http://blog.euromonitor.com/2016/10/estrategias-para-la-expansion-mercadosemergentes-utilizando-e-commerce.html. Accessed 26 Jan 2021
[7]
Burke R Do you see what I see? The future of virtual shopping J. Acad. Mark. Sci. 1997 25 4 352-360
[8]
Brown LG The strategic and tactical implications of convenience in consumer product marketing J. Cons. Market. 1989 6 13-20
[9]
Chiang, K.: Effects of price, product type, and convenience on consumer intention to shop online. In: American Marketing Association Conference Proceedings, Chicago, IL Winter, pp. 163–169 (2001)
[10]
Chiang K and Dholakia RR Factors driving consumer intention to shop online: an empirical investigation J. Cons. Psychol. 2003 13 1/2 177-183
[11]
Childers TL, Carr CL, Peck J, and Carson S Hedonic and utilitarian motivations for online retail shopping behavior J. Retail. 2001 77 511-535
[12]
CNN Chile. https://www.cnnchile.com/tendencias/la-verdadera-historia-tras-el-black-friday_20181123/. Accessed 26 Jan 2021
[13]
Cupani M Análisis de Ecuaciones Estructurales: conceptos, etapas de desarrollo y un ejemplo de aplicación Revista tesis 2012 1 1 186-199
[14]
CyberMonday. https://www.cybermonday.cl/info.html. Accessed 26 Jan 2021
[15]
Davis F Perceived usefulness, perceived ease of use and user acceptance of information technology MIS Quart. 1989 13 3 319-340
[16]
Ha S and Stoel L Consumer e-shopping acceptance: antecedents in a technology acceptance model J. Bus. Res. 2009 62 565-571
[17]
Hsu CL and Lu HP Why do people play on-line games? An extended TAM with social influences and flow experience Inform. Manage. 2004 41 7 853-868
[18]
Jarvenpaa, S.L., Todd, P.A.: Is there a future for retailing on the internet? In: Peterson, R.A. (ed.), Electronic Marketing and the Consumer, pp. 139–154. Sage, Thousand Oaks (1997)
[19]
Lee MC Explaining and predicting users’ continuance intention toward e-learning: an extension of the expectation–confirmation model Comput. Educ. 2010 54 2 506-516
[20]
Liao C, Chen JL, and Yen DC Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: an integrated model Comput. Hum. Behav. 2007 23 6 2804-2822
[21]
Liao C, Palvia P, and Chen JL Information technology adoption behavior life cycle: toward a Technology Continuance Theory (TCT) Int. J. Inf. Manage. 2009 29 4 309-320
[22]
Linio. https://www.linio.com.ar/sp/indice-ecommerce. Accessed 26 Jan 2021
[23]
Loewnthal KM An Introduction to Psychological Tests and Scales 1996 London UCL Press
[24]
Prieto, J.C.S., Migueláñez, S.O., García-Peñalvo, F.J.: Utilizarán los futuros docentes las tecnologías móviles? Validación de una propuesta de modelo TAM extendido. Revista de Educación a Distancia (52) (2017)
[25]
Rohm AJ and Swaminathan V A typology of online shoppers based on shopping motivations J. Bus. Res. 2004 57 7 748-757
[26]
Saura JR, Reyes-Menendez A, and Palos-Sanchez P Un Análisis de Sentimiento en Twitter con Machine Learning: Identificando el sentimiento sobre las ofertas de# BlackFriday Revista Espacios 2018 39 16 75
[27]
Shih H An empirical study on predicting user acceptance of e-shopping on the web Inf. Manage. 2004 41 351-368
[28]
Swaminathan, V., Lepkowska-White, E., Rao, B.P.: Browsers or buyers in cyberspace? An investigation of factors influencing likelihood of electronic exchange. J. Comput. Mediat. Commun. 5(2) (1999)
[29]
Swilley E and Goldsmith RE Black Friday and Cyber Monday: understanding consumer intentions on two major shopping days J. Retail. Cons. Serv. 2013 20 1 43-50
[30]
Tele13. https://www.t13.cl/noticia/tendencias/cyber-monday-2019-fecha? Accessed 26 Jan 2021
[31]
Venkatesh, V., Thong, J.Y., Xu, X.: Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quart. 157–178 (2012)
[32]
Vijayasarathy L Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model Inf. Manage. 2004 41 747-762
[33]
Weng GS, Zailani S, Iranmanesh M, and Hyun SS Mobile taxi booking application service’s continuance usage intention by users Transp. Res. Part D: Transp. Environ. 2017 57 207-216
[34]
Yong Varela, L.A., Rivas Tovar, L.A., Chaparro, J.: Modelo de aceptación tecnológica (TAM): un estudio de la influencia de la cultura nacional y del perfil del usuario en el uso de las TIC. Innovar. Revista de Ciencias Administrativas y Sociales 20(36) (2010)
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- Consumer Attitude and Behavior During Black Friday and Cyber Monday
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Published: 24 July 2021
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