Assessing differences in customers’ personal disposition to e-commerce

Pages792-820
DOIhttps://doi.org/10.1108/IMDS-07-2018-0280
Date13 May 2019
Published date13 May 2019
AuthorPatricio Esteban Ramírez-Correa,Elizabeth E. Grandón,Jorge Arenas-Gaitán
Subject MatterInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Assessing differences in
customerspersonal
disposition to e-commerce
Patricio Esteban Ramírez-Correa
School of Engineering, Universidad Católica del Norte, Coquimbo, Chile
Elizabeth E. Grandón
Department of Information Systems, Universidad de Bío-Bío, Concepción, Chile, and
Jorge Arenas-Gaitán
Department of Business Management and Marketing,
Universidad de Sevilla, Seville, Spain
Abstract
Purpose The purpose of this paper is to determine differences in customerspersonal disposition to
online shopping.
Design/methodology/approach The research model was proposed based on two types of purchases
(hedonic vs utilitarian) and on personal traits of individuals against technology throughout the Technology
Readiness Index (TRI) 2.0. Generation and gender were considered to evaluate their impact on the type of
purchases. Consumersdata were collected in Chile through 788 face-to-face surveys. The partial least squares
approach was used to test the research model.
Findings The findings show that optimism and discomfort influence online shopping.
Moreover, generati on and gender moderate t he relationship bet ween the dimensions o f the TRI and
online purchases.
Originality/value The contributions of this study are threefold. The analysis of personal traits and the
type of purchases contribute to the existing literature on consumer behavior and e-commerce, and provide
some insights for marketers to identify segmentation strategies by analyzing the gender and generation of
individuals. Second, this study contributes to examining the stability and invariances of the TRI 2.0
instrument, which has not been fully revised in less developed countries. Third,this study adds to the existing
body of research that argues that demographic variables are not sufficient to understand technology adoption
by individuals by including psychological variables.
Keywords E-commerce, Generation, Gender, Hedonic purchase, TRI 2.0, Utilitarian purchase
Paper type Research paper
1. Introduction
Almost 30 years after its emergence e-commerce is still a global phenomenon. However, the
expectations in its development have not been fully met; in fact, there are still significant
differences between online and offline purchases. For example, in the USA, more than
90 percent of consumer spending continues to occur offline (Glueck, 2017). Given this fact, to
explain in a better way what motivates people to make online purchases is a relevant issue,
even more so in the current hyper-technological context.
E-commerce, the process of buying and selling products or services using electronic
data transmission via the Internet and the www(Turban et al., 2011) has been widely
studied. The literature reports many studies that have focused on determining factors that
influence the adoption of e-commerce by small, medium and large enterprises (Gorla et al.,
2017; Grandón and Pearson, 2004; Rahayu and Day, 2015). Yet, less research has been
devoted to studying perceptions of e-commerce by individuals and even a smaller amount
has focused on relating individuals technological dispositions with the type of purchases
they make (Davis et al., 2013; Lee and Lyu, 2016). Therefore, more studies are required since
technological advancements continue to grow.
Industrial Management & Data
Systems
Vol. 119 No. 4, 2019
pp. 792-820
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-07-2018-0280
Received 4 July 2018
Revised 14 October 2018
30 November 2018
Accepted 22 December 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
792
IMDS
119,4
Personal characteristics are considered important to understand consumer behavior, in
particular age and gender. Nonetheless, and according to Peral-Peral et al. (2015), these
demographic characteristics are not sufficient to profoundly understand the motivations
that lead individuals to adopt technologies. In their study, Peral-Peral et al. (2015) considered
psychological variables to better comprehend the use of online social network by elder
citizens. They found that psychological variables complement socio-demographic variables
when explaining social network adoption.
As in the case of e-commerce, there is also a stream of research that has focused on
finding factors influencing hedonic purchases (associated with fun and joy) and utilitarian
purchases (associated with obligation). Kivetz and Zheng (2017) proposed that different
promotions, such as price discounts, rebates, coupons and loyalty rewards, have a stronger
positive effect on hedonic purchases than on utilitarian purchases. Similarly, Khan and Dhar
(2010) studied how price-framing influences hedonic and utilitarian bundles. On the other
hand, López and Ruiz (2011) considered attitude as a bi-dimensional construct comprised of
hedonic and utilitarian components, and tested the mediation effect of these components
between cognitions and emotions generated by a product and purchase intention.
Based on the aforementioned studies, it seems that there is a lack of research that has
used personal factors to explain hedonic and utilitarian online purchases and that has
related individuals technological dispositions with the type of purchases they make. This
is particularly important for developing countries which find many barriers to adopt
e-commerce (Lawrence and Tar, 2010; Daviy and Rebiazina, 2015; Kartiwi and MacGregor,
2007). For instance, only 37 percent of small- and medium-sized businesses have embarked
on e-commerce in Chile, even though it is considered the leading country in Latin America
according to the e-commerce index (Santiago Chamber of Commerce, 2016). At the
individual level, 66.01 percent of Chileans used the internet and 15.97 percent subscribed to
fixed-broadband in 2016 (ITU, 2017). Chile is a country with 18m people approximately,
where 66.5 percent of households have access to the internet and with an annual economic
growth of 1.6 percent (OECD, 2018). These facts make Chile a good case study for assessing
dispositions of consumers to embark on e-commerce.
Therefore, the aim of this study is to determine differences in customerspersonal
disposition to online shopping. Centered on the literature consulted, we first differentiated
behaviors among diverse types of purchases (hedonic vs utilitarian). Then, we addressed
personal traits of individuals against technology throughout the Technology Readiness
Index 2.0 (TRI 2.0) proposed by Parasuraman and Colby (2015). Finally, we analyzed the
influence of socio-demographic characteristics on the relationship between personality traits
and type of purchases individuals make. Particularly, the generation and gender of
individuals were considered to evaluate their impact on the type of purchases.
The contributions of this study are threefold. The analysis of personal traits and the type
of purchases contribute to the existing literature on consumer behavior and e-commerce,
and provide some insights for marketers to identify segmentation strategies by analyzing
the gender and generation of individuals. Second, this study contributes to examining the
stability and invariances of the TRI 2.0 instrument, which has not been fully revised in less
developed countries. Third, this study adds to the existing body of research that argues that
demographic variables are not sufficient to understand technology adoption by individuals
by including psychological variables.
The rest of the paper is structured as follows. Section 2 discusses the related literature
associated with hedonic and utilitarian purchases, the TRI and demographic differences in
online shopping. In addition, the research model and hypotheses are set out. Section 3
presents details of the data analysis methodology. Section 4 describes the results of the
study, and section 5 presents a discussion of these results. The final section draws
conclusions, limitations and future research.
793
Customers
personal
disposition to
e-commerce

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