Technology Acceptance Model in E-Commerce Segment
The assignment is about analyzing the changes in e-commerce trading patterns and marketplace models, with a focus on the impact of social commerce and the use of social media. The essay should critically evaluate the changes in consumer and business trading patterns, including industry structure, industry analysis, industry value chains, and firm value chains.
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Added on 2022-11-26
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This research paper focuses on the technology acceptance model in the context of e-commerce segment. It analyzes the impact of user experience factors on e-commerce websites and explores the use of modern technologies such as social networks and mobile apps. The study aims to create a model that explains the impact of each major factor on the user experience and the re-visit of the e-shop.
Technology Acceptance Model in E-Commerce Segment
The assignment is about analyzing the changes in e-commerce trading patterns and marketplace models, with a focus on the impact of social commerce and the use of social media. The essay should critically evaluate the changes in consumer and business trading patterns, including industry structure, industry analysis, industry value chains, and firm value chains.
Added on 2022-11-26
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Technology acceptance model in e-commerce segment
Igor FEDORKO
University of Prešov, Prešov, Slovak Republic
igor.fedorko@unipo.sk
Radovan BACIK
University of Prešov, Prešov, Slovak Republic
radovan.bacik@unipo.sk
Beata GAVUROVA
Research and Innovation Centre Bioinformatics, TECHNICOM, Kosice, Slovakia
Faculty of Economics, Technical University of Košice, Košice, Slovak Republic
beata.gavurova@tuke.sk
Abstract. Consumer behaviour analysis is a key aspect for the success of e-business. The main objective
of the study is to analyse the impact of selected user experience factors on e-commerce web site visiting
(technology). The objective of the study is to create a model that will explain the impact of each major
factor on the user experience and the re-visit of the e-shop. To explain the use of e-commerce
technology, in the second part we have modified the original technology acceptance model (TAM) with
other constructs. Specifically, there are modern technologies such as social networks or mobile apps
that affect the use of e-shops. The TAM model is one of the most used models of what the system uses to
identify the perceived usefulness and perceived simplicity of use from the user' side. For the main
advantage of our study, we consider that we have highlighted the importance of the factor of modern
technology and therefore of social networks, mobile applications and contextual advertising. This
factor, along with the other two factors, has been incorporated into our model and has shown that
modern technologies have a direct impact and are therefore directly related to the frequency using the
e-commerce websites.
Keywords: TAM, consumer behavior, e-commerce, user experience.
Please cite the article as follows: Fedorko, I., Bacik, R. & Gavurova, B. (2018), “Technology
Acceptance Model in E-Commerce Segment”, Management & Marketing. Challenges for the
Knowledge Society, Vol. 13, No. 4, pp. 1242-1256, DOI: 10.2478/mmcks-2018-0034.
Introduction
By 2020, four billion people are expected to be online, suggesting that addressing
customers’ needs will be more important than ever (IDC, 2015). Marketers needs to
continually improve business strategies and models (Ungerman et al., 2018). With the
advancement of digital platforms, online shopping environments are evolving as well, and
they are able to offer consumers more options in the purchase process, providing them with
better services and products (Pappas, 2018). It is important to identify the reasons that
customers choose to visit an online store and following their shopping motivations. It ist
important to understand how their behavior differs based on their predisposition towards
modern online shopping. Many theories and models have been proposed over the years to
explain the individuals' usage behavior towards technologies (Momani et al., 2017). This
research paper focuses on the technology acceptance model in context of e-commerce
Igor FEDORKO
University of Prešov, Prešov, Slovak Republic
igor.fedorko@unipo.sk
Radovan BACIK
University of Prešov, Prešov, Slovak Republic
radovan.bacik@unipo.sk
Beata GAVUROVA
Research and Innovation Centre Bioinformatics, TECHNICOM, Kosice, Slovakia
Faculty of Economics, Technical University of Košice, Košice, Slovak Republic
beata.gavurova@tuke.sk
Abstract. Consumer behaviour analysis is a key aspect for the success of e-business. The main objective
of the study is to analyse the impact of selected user experience factors on e-commerce web site visiting
(technology). The objective of the study is to create a model that will explain the impact of each major
factor on the user experience and the re-visit of the e-shop. To explain the use of e-commerce
technology, in the second part we have modified the original technology acceptance model (TAM) with
other constructs. Specifically, there are modern technologies such as social networks or mobile apps
that affect the use of e-shops. The TAM model is one of the most used models of what the system uses to
identify the perceived usefulness and perceived simplicity of use from the user' side. For the main
advantage of our study, we consider that we have highlighted the importance of the factor of modern
technology and therefore of social networks, mobile applications and contextual advertising. This
factor, along with the other two factors, has been incorporated into our model and has shown that
modern technologies have a direct impact and are therefore directly related to the frequency using the
e-commerce websites.
Keywords: TAM, consumer behavior, e-commerce, user experience.
Please cite the article as follows: Fedorko, I., Bacik, R. & Gavurova, B. (2018), “Technology
Acceptance Model in E-Commerce Segment”, Management & Marketing. Challenges for the
Knowledge Society, Vol. 13, No. 4, pp. 1242-1256, DOI: 10.2478/mmcks-2018-0034.
Introduction
By 2020, four billion people are expected to be online, suggesting that addressing
customers’ needs will be more important than ever (IDC, 2015). Marketers needs to
continually improve business strategies and models (Ungerman et al., 2018). With the
advancement of digital platforms, online shopping environments are evolving as well, and
they are able to offer consumers more options in the purchase process, providing them with
better services and products (Pappas, 2018). It is important to identify the reasons that
customers choose to visit an online store and following their shopping motivations. It ist
important to understand how their behavior differs based on their predisposition towards
modern online shopping. Many theories and models have been proposed over the years to
explain the individuals' usage behavior towards technologies (Momani et al., 2017). This
research paper focuses on the technology acceptance model in context of e-commerce
MMCKS
1243
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
segment. Technology acceptance has become one of the most significant subjects in
software engineering field.
Literature review
Lacking the presence of human and social elements is claimed one major weakness that is
hindering the growth of e-commerce. Social commerce is a new evolution of e-commerce
that combines the commercial and social activities by deploying social technologies into e-
commerce sites (Lu et al., 2015). As a relatively new phenomenon, social commerce has
evolved quickly in practice (Barnes, 2014; Kim & Park, 2013; Wang & Zhang, 2012). The
present study focuses specifically on the verbal format of online product information and
examines its impact on selected aspects of the online shopping experiences (Eroglu,
Machleit, & Davis, 2003). The central premise is that consumers' perceptual fluency of the
verbal information presented online is a key factor that shapes their perceived cognitive
effort, positive affect, and, ultimately, their choice outcome judgments in the virtual
shopping context (Mosteller, Donthu, & Eroglu, 2014; Reber, Schwarz, & Winkielman,
2004). Online retailers have been implementing various strategies to attract and retain
customers. Web personalization has been identified as an important factor in the area of
marketing and information systems (Salonen and Karjaluoto, 2016). Consumer behaviour
analysis is a key aspect for the success of e-business. However, consumer behaviour
towards changes in the Internet market changes as users gain experience (Gefen et al.,
2003; Yu et al., 2005; Gavurova et al., 2018). Perceptions that affect their electronic
purchase can have different impacts on consumer choice or buyback, because the use of
information technology (IT) can change based on perceptions and attitudes (Gefen, 2003).
Salovaara (2009) states that when monitoring the UX, we can talk about the perception and
responsiveness of the person resulting from the use of the product, system or service.
Hassenzahl (2007) describes the user experience as a consequence of the user's internal
state (disposition, expectation, motivation, mood), but also the characteristics of the
proposed system (complexity, purpose, usability, functionality) and last but not least the
context in which the interaction occurs (e. g. social background, organizational background,
voluntary use). We can define UX as a user experience that includes all aspects of final-user
interaction with the specific e-shop and the services and products it sells (Stefko et al.,
2011). Analysing the number of visitors is considered a very important tool in UX
measurement. Evaluators can use different metrics that apply to the different areas and
features of the software we want to measure. The most commonly measured and tracked
are the following: Measure the success of the key tasks – which is the metric that is
considered to be the basic usability metric of the software, website or e-capability. If the
user is unable to complete the given task, the other application or page properties are
irrelevant. This means that the successful completion of a task depends on the type of the
task. In primary tasks, their success is expected to be 100%, while in secondary tasks it is a
utopia (Sauro, 2011). There are many e-shops on the internet whether in Slovakia or
abroad that offer similar and often the same products or services. Therefore, it is also
advisable to analyse the competitive environment in order to differ from the competitors
and how to engage the customers as much as possible. When analysing the competitors, we
focus on the usability, functionality and opportunity analysis (Hawley, 2012). Hawley
(2012) also brings out the characteristics of these approaches: usability analysis - its main
purpose is to detect the errors made by a competing website. However, here we may
1243
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
segment. Technology acceptance has become one of the most significant subjects in
software engineering field.
Literature review
Lacking the presence of human and social elements is claimed one major weakness that is
hindering the growth of e-commerce. Social commerce is a new evolution of e-commerce
that combines the commercial and social activities by deploying social technologies into e-
commerce sites (Lu et al., 2015). As a relatively new phenomenon, social commerce has
evolved quickly in practice (Barnes, 2014; Kim & Park, 2013; Wang & Zhang, 2012). The
present study focuses specifically on the verbal format of online product information and
examines its impact on selected aspects of the online shopping experiences (Eroglu,
Machleit, & Davis, 2003). The central premise is that consumers' perceptual fluency of the
verbal information presented online is a key factor that shapes their perceived cognitive
effort, positive affect, and, ultimately, their choice outcome judgments in the virtual
shopping context (Mosteller, Donthu, & Eroglu, 2014; Reber, Schwarz, & Winkielman,
2004). Online retailers have been implementing various strategies to attract and retain
customers. Web personalization has been identified as an important factor in the area of
marketing and information systems (Salonen and Karjaluoto, 2016). Consumer behaviour
analysis is a key aspect for the success of e-business. However, consumer behaviour
towards changes in the Internet market changes as users gain experience (Gefen et al.,
2003; Yu et al., 2005; Gavurova et al., 2018). Perceptions that affect their electronic
purchase can have different impacts on consumer choice or buyback, because the use of
information technology (IT) can change based on perceptions and attitudes (Gefen, 2003).
Salovaara (2009) states that when monitoring the UX, we can talk about the perception and
responsiveness of the person resulting from the use of the product, system or service.
Hassenzahl (2007) describes the user experience as a consequence of the user's internal
state (disposition, expectation, motivation, mood), but also the characteristics of the
proposed system (complexity, purpose, usability, functionality) and last but not least the
context in which the interaction occurs (e. g. social background, organizational background,
voluntary use). We can define UX as a user experience that includes all aspects of final-user
interaction with the specific e-shop and the services and products it sells (Stefko et al.,
2011). Analysing the number of visitors is considered a very important tool in UX
measurement. Evaluators can use different metrics that apply to the different areas and
features of the software we want to measure. The most commonly measured and tracked
are the following: Measure the success of the key tasks – which is the metric that is
considered to be the basic usability metric of the software, website or e-capability. If the
user is unable to complete the given task, the other application or page properties are
irrelevant. This means that the successful completion of a task depends on the type of the
task. In primary tasks, their success is expected to be 100%, while in secondary tasks it is a
utopia (Sauro, 2011). There are many e-shops on the internet whether in Slovakia or
abroad that offer similar and often the same products or services. Therefore, it is also
advisable to analyse the competitive environment in order to differ from the competitors
and how to engage the customers as much as possible. When analysing the competitors, we
focus on the usability, functionality and opportunity analysis (Hawley, 2012). Hawley
(2012) also brings out the characteristics of these approaches: usability analysis - its main
purpose is to detect the errors made by a competing website. However, here we may
MMCKS
1244
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
encounter the risk that the errors we find on a competing website will not help solve the
problem. Functionality Analysis - This analysis is about features used by competitors on
their website, which determine whether these features benefit their website. This is a so-
called brainstorming, but we are experiencing the risk that our opinion on the problematic
area may be affected and we will accept this solution instead of finding the most effective
one. Opportunity analysis - This is a creative approach that looks for a variety of
innovations and suggestions for competitors and their e-commerce websites to discover
new opportunities for their website.
Methodology and database
The main objective of the study is the realization of a survey that will focus on the specific
opinions and preferences of the respondents in relation to the influence of the user
experience on e-commerce websites (technology). E-commerce websites want users to
achieve their goals after visiting the page and have a positive user experience by using the
website. So that they do not feel frustrated when using it during the first time (and later
on). These negative feelings can result in a lengthy search for the necessary information or
a complicated website orientation. The objective of the study is to create a model that will
explain the impact of each major factor on the user experience and the re-visit of the e-shop.
To explain the use of e-commerce technology, in the second part we have modified the
original TAM model with other constructs. Specifically, modern technologies such as social
networks, mobile apps and online advertising have an impact on the use of e-shops. At the
same time, we extend the model by factors that significantly affect the perceived usefulness
and perceived simplicity of use. Based on the objectives of the analytical part and the
definition of the research problems, we formulated six hypotheses. The TAM Model (Figure
1) is one of the most used models of what the system uses to identify the perceived
usefulness and perceived simplicity of use. Perceived usefulness expresses the likelihood of
a prospective user who assumes that certain applications can increase user performance.
The perceived simplicity of use is defined by the degree to which the potential user expects
to control the system effortlessly (Davis et al.,1989).
Figure 1. Technology acceptance model
Source: Adapted from Davis et al., 1989.
Previous research has mainly focused on understanding the psychological and
sociological factors that will shape an individual's behavioral intention toward using
technology (Venkatesh et al. 2003). Based upon conceptual and empirical similarities
1244
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
encounter the risk that the errors we find on a competing website will not help solve the
problem. Functionality Analysis - This analysis is about features used by competitors on
their website, which determine whether these features benefit their website. This is a so-
called brainstorming, but we are experiencing the risk that our opinion on the problematic
area may be affected and we will accept this solution instead of finding the most effective
one. Opportunity analysis - This is a creative approach that looks for a variety of
innovations and suggestions for competitors and their e-commerce websites to discover
new opportunities for their website.
Methodology and database
The main objective of the study is the realization of a survey that will focus on the specific
opinions and preferences of the respondents in relation to the influence of the user
experience on e-commerce websites (technology). E-commerce websites want users to
achieve their goals after visiting the page and have a positive user experience by using the
website. So that they do not feel frustrated when using it during the first time (and later
on). These negative feelings can result in a lengthy search for the necessary information or
a complicated website orientation. The objective of the study is to create a model that will
explain the impact of each major factor on the user experience and the re-visit of the e-shop.
To explain the use of e-commerce technology, in the second part we have modified the
original TAM model with other constructs. Specifically, modern technologies such as social
networks, mobile apps and online advertising have an impact on the use of e-shops. At the
same time, we extend the model by factors that significantly affect the perceived usefulness
and perceived simplicity of use. Based on the objectives of the analytical part and the
definition of the research problems, we formulated six hypotheses. The TAM Model (Figure
1) is one of the most used models of what the system uses to identify the perceived
usefulness and perceived simplicity of use. Perceived usefulness expresses the likelihood of
a prospective user who assumes that certain applications can increase user performance.
The perceived simplicity of use is defined by the degree to which the potential user expects
to control the system effortlessly (Davis et al.,1989).
Figure 1. Technology acceptance model
Source: Adapted from Davis et al., 1989.
Previous research has mainly focused on understanding the psychological and
sociological factors that will shape an individual's behavioral intention toward using
technology (Venkatesh et al. 2003). Based upon conceptual and empirical similarities
MMCKS
1245
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
across prior technology adoption models, Venkatesh et al. (2003) developed the UniJied
Theory of Acceptance and Use of Technology (UTAUT).
Geften and Pavlou (2003) in their study claim that the original TAM model does not
capture all the factors that affect e-shop purchasing. Therefore, other factors such as
Internet experience, normative conviction, and online shopping experience have been
added to the model in addition to personal characteristics (age, gender, education). In our
survey, we focus on factors that influence the perceived usefulness, simplicity of use and
modify the original TAM model by other factors that could influence the usefulness and
simplicity of use. Our hypotheses:
H1: The quality of information significantly influences the perceived usefulness.
H2: Quality of service has a significant impact on perceived usefulness.
H3: Modern technologies significantly influence the perceived simplicity of use.
H4: The quality of the system significantly influences the perceived simplicity of use.
H5: Perceived usefulness has a significant impact on the use of technology.
H6: Perceived simplicity of use has a significant impact on the use of technology.
In order to meet the set goal, we used the exploration method to obtain the
necessary data. Using online questionnaires, we will source resources based on the
subjective responses of Internet users and users of e-commerce websites. The
questionnaire, which focused on finding satisfaction and perceived usefulness, had 27
questions. The first part of the questionnaire is based on basic demographic issues, with
which we have identified age, gender, education and economic status of users.
Subsequently, we found the attitudes and opinions of respondents on the quality of
information, service, website system and whether they are happy with the modern
technologies that e-commerce websites use to support their marketing communications or
not.
The questionnaire included closed questions where respondents could express their
degree of agreement or disagreement with the statement in a five-step Likert scale. To
obtain the necessary answers, we used a proportional stratified selection. We shared the
online questionnaire among respondents, especially through social media, but the most
preferred one was the Facebook social network. The questionnaire was anonymous and the
respondents filled it voluntarily. We have decided to analyze the reliability of the research
file in a number of ways. The first method was test - retest, repeating the administration of
the research group. When repeating the administration, we proceeded by submitting the
same respondents after a certain period of time to the same questionnaire survey and to
monitor the degree of agreement between the observations. The degree of correspondence
between the two results was expressed by the correlation coefficient, with all the results we
measured high values above 0.80. As our survey does not consist of dichotomous items but
has a larger span of scoring, we have tracked the Cronbach alpha coefficient. To evaluate
the survey data, we used the R Studio software, which we used to calculate the Pearson
correlation coefficients for each variable. We then presented the results using charts and
tables. In the summary table, using the lower triangle method, we calculated the values that
were confirmed by the dependence of the hypotheses.
Nowadays, purchasing goods and services on the Internet is a very common practice
of people around the world. Some prefer purchasing on the internet due to the comfort of
home, others due to the competitive price that e-commerce offers compared to physical
1245
Vol. 13, No. 4, Winter, pp. 1242-1256, ISSN 1842-0206 | Management & Marketing. Challenges for the Knowledge Society
across prior technology adoption models, Venkatesh et al. (2003) developed the UniJied
Theory of Acceptance and Use of Technology (UTAUT).
Geften and Pavlou (2003) in their study claim that the original TAM model does not
capture all the factors that affect e-shop purchasing. Therefore, other factors such as
Internet experience, normative conviction, and online shopping experience have been
added to the model in addition to personal characteristics (age, gender, education). In our
survey, we focus on factors that influence the perceived usefulness, simplicity of use and
modify the original TAM model by other factors that could influence the usefulness and
simplicity of use. Our hypotheses:
H1: The quality of information significantly influences the perceived usefulness.
H2: Quality of service has a significant impact on perceived usefulness.
H3: Modern technologies significantly influence the perceived simplicity of use.
H4: The quality of the system significantly influences the perceived simplicity of use.
H5: Perceived usefulness has a significant impact on the use of technology.
H6: Perceived simplicity of use has a significant impact on the use of technology.
In order to meet the set goal, we used the exploration method to obtain the
necessary data. Using online questionnaires, we will source resources based on the
subjective responses of Internet users and users of e-commerce websites. The
questionnaire, which focused on finding satisfaction and perceived usefulness, had 27
questions. The first part of the questionnaire is based on basic demographic issues, with
which we have identified age, gender, education and economic status of users.
Subsequently, we found the attitudes and opinions of respondents on the quality of
information, service, website system and whether they are happy with the modern
technologies that e-commerce websites use to support their marketing communications or
not.
The questionnaire included closed questions where respondents could express their
degree of agreement or disagreement with the statement in a five-step Likert scale. To
obtain the necessary answers, we used a proportional stratified selection. We shared the
online questionnaire among respondents, especially through social media, but the most
preferred one was the Facebook social network. The questionnaire was anonymous and the
respondents filled it voluntarily. We have decided to analyze the reliability of the research
file in a number of ways. The first method was test - retest, repeating the administration of
the research group. When repeating the administration, we proceeded by submitting the
same respondents after a certain period of time to the same questionnaire survey and to
monitor the degree of agreement between the observations. The degree of correspondence
between the two results was expressed by the correlation coefficient, with all the results we
measured high values above 0.80. As our survey does not consist of dichotomous items but
has a larger span of scoring, we have tracked the Cronbach alpha coefficient. To evaluate
the survey data, we used the R Studio software, which we used to calculate the Pearson
correlation coefficients for each variable. We then presented the results using charts and
tables. In the summary table, using the lower triangle method, we calculated the values that
were confirmed by the dependence of the hypotheses.
Nowadays, purchasing goods and services on the Internet is a very common practice
of people around the world. Some prefer purchasing on the internet due to the comfort of
home, others due to the competitive price that e-commerce offers compared to physical
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