The Importance Of Applying Contactless Technologies In Event Practices During Covid-19 Pandemic Towards Customer Attitudes.docx

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The importance of applying contactless technologies in event practices during covid-19
pandemic towards customer attitudes
Abstract 1
1. Introduction 2
1.1 The business issue and the purpose of the project 2
1.2 Background to the study 4
1.3 Structure of the remainder of the report 5
2. Review of the literature 7
2.1 Contactless technology application in event practices 7
2.2 Covid-19 pandemic affecting to event practices 7
2.3 Contactless technology application towards customer attitudes 8
2.4 Model proposal 9
3. Methodology 11
3.1 Identification of paradigm 11
3.2 Justification for choice of methodology and methods 12
3.3 Limitations of the research design 13
4. Findings/Results 14
4.1 Cronbach’s alpha 14
4.2 EFA 19
4.3. Regression analysis 20
5. Conclusion 23
5.1 Summary of what you found out in relation to each research question you investigated
Your contribution to the existing body of knowledge on the chosen business issue 23
5.2 Limitations of research and suggestions for future research 24
5.3 Implications of your research for practice 25
References UWE Harvard 25
Appendix 27
Abstract
Digital-based contactless services are gradually replacing face-to-face services. The
extremely rapid transition from direct contact to contactless, due to the impact of the Covid 19
epidemic, has become a major problem globally. In that context, many countries have

considered promoting the application of contactless technology in many issues of social life.
To catch up with the transition to the contactless market; Many businesses also focus on
developing non-contact services close to daily life, such as medical care, education, business,
consumption, entertainment, logistics and distribution, information and security. security,
transportation and increased global competition. In which, many events are also promoted to
apply contactless technologies and services. Customer acceptance and attitudes towards the use
of non-contact technologies for the event sector are critical to consumer and corporate business
practices. Therefore, this study investigates the application of contactless technology to the
operation of events during the Covid 19 epidemic; influence on customer attitudes. This study
performed an assessment of customer consent and consent; as well as customer attitudes toward
the use of contactless technologies. In which, the research factors affecting the customer's
attitude; includes six independent variables: effort expectancy, performance expectancy,
facilitating conditions, hedonic motivation, price value, and social influence.
1. Introduction
1.1 The business issue and the purpose of the project
Retailers, restaurateurs, hotels and other businesses centered on providing hospitable
experiences know better than most how challenging it has become to connect to customers in
recent months. For the most part, interactions have become purely transactional with people
afraid to get too close to one another or linger too long. Customers who do walk into brick-
and-mortar stores or restaurants these days tend to be focused on getting what they need and
getting out as quickly and safely as possible. Some curbside customers don’t even crack their
windows to say hello, instead resorting to a friendly wave through the window. And workers
delivering food, groceries and parcels to customers’ homes have probably never seen the people
they’re serving since many customers wait until the delivery person has stepped far away from
the door – or even driven away – before retrieving their items. Even hoteliers report limited
contact with guests, many of whom quickly beeline it to self-check-in and then their rooms
(Rahimizhian and Irani, 2020).
According to research by the Professional Events organization (2020); a unit
specializing in organizing large events in Vietnam has shown a lot of potential in developing
and applying contactless technology in the field of event organization during the outbreak of
the COvid 19 epidemic. This organization's assessment includes Face recognition, fingerprint
application, AI application, 3D design event diagram, Game application, VENUE SOURCING
PLATFORM; and WEARABLE TECH. FACE REMOVAL Through the application and use
of images uploaded during the registration process, facial recognition technology helps to

record the facial features of each attendee. This technology helps personalize user information,
such as printing name tags when attending a program, emailing invitations, tickets to attend or
lunch tickets at the event. Facial recognition can do two things: register properly and provide
contactless entry for customer events. Facial recognition enables contactless registration, which
means the technology will only grow in popularity in the coming months and years.
EVENT FINDING applies RFID and Beacon technology, event organizers can collect
user information and personalize each event experience for attendees. Participants can view the
event agenda, and the organizer will announce the program's time for guests to come and attend.
AI applications are like websites that use AI to feed their tools, event planning software has
started to use AI to assist in finding attendees, speakers, speakers, etc. influence, topic, and
suggest optimal time and place. AI-powered chatbots can be used for pre-event
communications and customer service to answer common questions, automate ticket sales, and
track leads. 3D EVENT MAP indicates that a favorable event needs to ensure details of the
layout such as seating, lighting, zones and rooms within the framework. With 3D event
mapping software, event organizers can easily create an accurate 3D diagram, customizable to
program design or scale. GAME APPLICATION or Gamification is one of the most exciting
ways to bring attendees to the event. Understanding the preference for rewards and competition
among attendees, we can engage attendees by leveraging the adoption of games in the event.
VENUE SOURCING PLATFORM indicates that event organizers are turning to event venue
supply platforms. These platforms will connect directly to the appropriate websites for each
event theme, organizers can submit bids and monitor the event management process. This
technology helps event organizers easily access at any time, have an overview of the event
model, capacity, and services provided. Once the venue is selected, the organizer can submit a
request and immediately receive a quote to start the event. Finally, WEARABLE TECH are
take-away technologies that are becoming more common and helping to improve the attendee
experience. Along with many convenient applications, the application of wearable tech to
events is a trend that many organizers are aiming for. With just one action, users can completely
exchange information in networking sessions to focus more on the conversation and create
more relationships with people.
Hao (2021) pointed out that the application of contactless technologies can be
considered an effective initiative during the Covid 19 epidemic. In this period, the application
of technologies to continue to ensure the process Work is inevitable. There have been many
technological applications developed in many fields in the past period, applied in many
different fields. Although the application prospect is potential, the application also needs to

consider the acceptance and attitude of customers on this issue. Skift (2020) indicates that some
customers do not really believe that contactless technology can increase service experience and
quality; like what they wanted. Ben (2021) assessed that many customers only consider short-
term mandatory contactless technology applications, which are affected by the Covid 19
epidemic. Therefore, this study was developed and established. aimed at assessing guests'
attitudes when organizing practical events; when applying technology does not continue. From
there, this study proposes and develops a number of solutions to promote positive customer
attitudes; improve service quality through customer's perception and evaluation.
1.2 Background to the study
The explosive trend of digital technology has given rise to many new economic models
such as circular economy, sharing economy and creative economy. In particular, the outbreak
of the Covid-19 pandemic has been and will affect not only human health but also all activities
of working, living, eating, resting, shopping, exercising. and spend leisure time on a global
scale. The longer the pandemic lasts, the longer the epidemic prevention measures are applied,
the more likely people are to form new habits that disrupt the economy. The coming years will
be shaped by digital technology trends and the current crisis. Although in the recent period, the
epidemic has been effectively controlled; It may take some time for people and businesses to
get back to normal activities.
Modern event management technologies are gradually creating new trends, bringing
unique and interesting experiences to attendees. Instead of organizing events in the same way
that is too boring and familiar, many businesses have proactively picked up on this trend,
catching up with the trend of technology transformation in the new era. The 4.0 technology
revolution and the explosion of contactless event technologies have brought great changes in
the way and behavior of technology is used. Technology devices have never been more popular
and developed as quickly as they are now. Now, we can completely see, experience, interact in
virtual spaces or witness great performances through technology applications at events. Many
modern event technologies are constantly emerging and are shaping a new future for the events
industry.
Though this level of avoidance would have been considered rude before COVID-19,
most people now accept deliberate physical distancing and sharp dialogue as necessary. At
least for now. There’s an appreciation and respect for others’ cautiousness when interacting in
person as we all do our part to curb the spread of the virus. That being said, there’s a difference
between creating distance and disengaging all together. The customer experience still remains

a top influencer in consumers’ shopping and dining decisions, and businesses’ ability to sustain
operations long term is dependent on their ability to meet each customer’s unique needs (Min,
2020). Although connecting with customers “in person” has been a challenge, rapid innovation
is now making it possible. “Low-touch” business activities do not require large gatherings or
close interaction with customers. This industry group has been doing quite well during the
COVID-19 pandemic, as online shopping, online education, online entertainment and cashless
payments have witnessed unprecedented growth even in the US. Vietnam and abroad (Pillai,
Haldorai, Seo and Kim, 2021).
However, these changes happened quite quickly due to the impact of the Covid 19
epidemic. It is necessary to study and evaluate the attitude and approval of customers; to
examine the development prospects and sustainability of contactless technology applications.
The lasting impact of Covid-19 has significantly changed the consumption habits of customers
in all fields, including event organization. Although service quality and connectivity can be
promoted, along with experience requirements, customers need to be met and service quality
guaranteed; as well as ensure convenience for customers. To meet this need, contactless
technology is considered as the right solution for the future prospect. At the same time, it is
also a suitable direction to help businesses and customers apply in the next period.
1.3 Structure of the remainder of the report
This section describes the evolving structure of this study. Content includes the list of
chapters and the contents of the displayed chapters.
Specifically, there are five main chapters in this study:
Part 1: Introduction
This section provides an overview of the research area and the key issues analyzed.
Specific factors include research overview, research scope and target analysis audience and
significance of the study; and then give contributions and conclusions for the purpose of this
study. Research questions are brief and focused on the research problem. Research methods
are approached to be used in the most effective way to solve research problems. Finally, this
section outlines the overall structure of the study and introduces the subsections that follow.
Part 2. Review of the literature
All theoretical and conceptual frameworks are provided in this chapter. Specifically,
the research model will be shown to indicate the hypothesis with the theoretical basis for each
structure. This section provides brief but comprehensive summaries of previous studies with a
unified research theme. Research focuses on prestigious journals in the world and especially
important economic fields. The content of this chapter talks about the trend of application of

contactless technology and the impact of the Covid-19 epidemic on the organization of events.
Furthermore, this section presents an underlying theoretical framework to help shape the
underlying issues that this study focuses on. The literature review focuses on the years close to
when this study was developed. Finally, the study builds a theoretical basis and a standard
framework for the model that this study develops.
Part 3. Methodology
This study was built to evaluate the interrelated factors as well as the interaction
between these factors. In it, hypotheses are developed to test the relationships between
variables; whether the relationship between these variables is a correlation relationship or not.
In addition, this chapter describes how this study was conducted. In more detail, the author's
method of forming a survey for data collection, sampling and data analysis will be presented
in this chapter. The main content of this chapter is the research methods used in the analysis of
this study. In which research methods are carried out are analytical techniques and other
evaluation procedures.
Part 4. Findings/Results
This section introduces the results carried out and analyzed from the research model.
Assumptions about model effectiveness are made to ensure that the model is statistically and
economically meaningful. From the results of the analysis and research in the previous section,
the researcher analyzes and evaluates some of the results and discusses the results in this study.
First, the author will confirm the results with other studies in the past to point out differences
or similarities between this study and previous research. After that, all research questions will
be answered and some assessment will be given to prospective applications of contactless
technology in the future and which factors affect customer attitudes. Then, as a result of the
research, some recommended or suggested actions to make contactless technology application
services better will be provided; to deliver an adaptive customer experience.
Part 5. Conclusion
This section summarizes and summarizes the research issues, evaluates the unresolved
limitations. From that point out some future development directions for possible follow-up
studies. The main purpose of this chapter is to summarize all the research processes,
summarizing what has been archived by this research. Besides, this chapter points out the main
contributions of the study as well as points out some limitations that can be improved in future
research.

2. Review of the literature
2.1 Contactless technology application in event practices
In the current era of industrialization and modernization, the application of contactless
technology has brought many influences in many fields such as education, healthcare, working
environment, payment system; In particular, it has made a great influence in the practice of
events. Researchers have shown that contactless technology is applicable at almost all stages
of the event journey. Event organizers can use contactless technology to increase engagement
and control activity within and outside of their premises. Researchers have shown that recently
government agencies and organizations are using contactless technology across all sectors, thus
being able to establish and demonstrate relationships with their clients (Menze, 2020).
This contactless technology is also flexibly applied in developing countries; include
technologies that are quickly accessible to users or organizations; so this technology directly
affects their behavior, attitude and way of life. In addition, contactless technology helps satisfy
even the most demanding consumers, providing accurate information and reacting quickly to
fluctuations in event practices (Hao, Xiao and Chon, 2020). Researchers have demonstrated
that online capabilities and applications are used by event organizers; so they are shaping,
developing and driving more event experiences through contactless technology (Kim, Kim and
Hwang, 2021).
Digital technology, social media channels, mobile applications are contactless
technologies that directly impact event design. Not only creating economic benefits, but
applying this technology also brings great cultural value; it helps participants in the same event
to increase their online friendship through the event photos being commented on and shared
widely in the community (Shawaqfeh, Alqaied and Jaradat, 2019). In addition, in order to
reduce daily work, communicate with friends quickly and communicate in business effectively,
users have applied contactless technology through smart devices. However, contactless
technology is still relatively new and needs to be developed, upgraded, improved continuously
and expanded in developing countries around the world (Stalmachova, Chinoracky and
Strenitzerova, 2022).
2.2 Covid-19 pandemic affecting to event practices
In recent years, the Covid - 19 pandemic has caused an economic - cultural crisis for
almost every country in the world; where event practices are also severely affected. The
COVID-19 pandemic presents many challenges for event practices because when a pandemic
occurs, national governments take measures to limit the movement of people, prohibit
gatherings to cause disease spread, at the same time closing the border for quarantine. Together

with these restrictions, the market crashed suddenly, causing a significant reduction in profits.
During the pandemic, most events were canceled or suspended; that caused the event industry
to enter a period of serious crisis. The Covid -19 pandemic has impacted a period of uncertainty
for the events industry and has had major consequences for the industry; therefore, the event
organization companies in particular and the event industry in general are struggling to find
ways to cope with the current situation and find new opportunities to develop. Recent studies
around the world have shown that the covid-19 pandemic has a strong impact on event
practices. Most events in the country have been postponed, canceled, suspended and scaled
down due to the pandemic; that affects not only the events industry but also related industries
(Stalmachova, Chinoracky and Strenitzerova, 2022).
COVID-19 has strongly affected the global market and different industries, although
leaders have come up with timely solutions, efforts still have to be made to find and come up
with new solutions. to maintain and develop in this condition. Especially in practice, the event
poses many challenges worthy of attention, requiring the intervention of the government and
event organizers.Everyone realizes the importance of safety and is becoming more and more
cautious in travel; however, this restriction has a negative impact on the world economy. A
survey in Wales found an average loss of £50,001 - £100,000 due to the event business in the
territory. Several international organizations have calculated and outlined the impacts of
Covid-19 on certain segments of the events industry on a global level. Covid-19 for event
practices has shown the magnitude of the impact on the disastrous economy (Chief Digital
Officers, 2021).
2.3 Contactless technology application towards customer attitudes
People's lives are gradually changing significantly, especially after the crisis of the
covid-19 pandemic, so contactless technology was born to help people regulate and balance
their lives. It brings positive effects and enjoyable experiences through helping people avoid
contact with surfaces like paper money, limiting the spread of disease. Not only that,
contactless technology helps to meet demand and boost supply, thereby reducing people's fear
of contracting Covid-19. In a recent survey, it was shown that the number of people who prefer
contactless related services such as alcohol dispensers, contactless soap, contactless faucets is
up to 95%. People feel excited when using these products to ensure their health and safety in
the face of complicated developments of the pandemic (OECD, 2020).
According to recent studies on consumer payment attitudes, the number of people who
know about contactless payment technology is up to 50%, of which 30% of people have used
it and 2/3 of people are ready. try using this form as an alternative to using cash. This

contactless technology is also widely applied in the fashion and beauty industries. Contactless
technology is increasingly growing in stores today; therefore, as a means to replace cash, it has
helped the stores to be flexible in the operation process; at the same time creating significant
changes to optimize customer needs. So contactless technology stimulates curiosity and
customer experience because it brings safe and fast transactions to customers.
Recent research has shown that attitude towards behavior affects intention to use
contactless technology although they have a negligible relationship. The researcher has shown
that the usefulness and ease of use of contactless technology is impacting the customer's
behavioral consciousness; At the same time, it also emphasizes the development of the current
economic situation. According to this study, contactless technology is being influenced by
customer attitudes.Contactless technology brings many benefits, positively affecting customer
attitudes, but also causes certain effects. Customers cannot control nor have the conditions to
check the problems related to money, time and effort. Therefore, the link between contactless
technology and customer attitudes was affected when the above issues occurred. Therefore, the
survey has shown potential influences on customer attitudes and orientation for the application
of contactless technology.
Customers' trust is available, but it is easily affected by the influence of the relationship
between the environment and the behavior of accepting the use of contactless technology.
Researchers have shown that trust in contactless technology has a relatively large impact on
customer attitudes. Customers do not really trust when using this technology because it brings
many risks, especially in the issue of using contactless technology to pay instead of using cash.
However, the crisis of the covid 19 pandemic has affected most sectors as the government has
enacted measures to avoid the spread. Customers easily get sick when they can come into
contact with easily contaminated surfaces; so they fear the risk of this contagion. The
researchers acknowledge that this fear has influenced decisions to use contactless technology
in most fields. Aware of the serious impact and risk of epidemics mentioned above, customers
are more motivated to access contactless technology and use it to meet customer needs.
2.4 Model proposal
Based on previous content and research, this study proposes variables affecting
Customers' acceptance and usage of innovative technology including 6 variables: Effort
expectancy, Performance expectancy, Facilitating conditions, Hedonic motivation, Price value,
Social influence.

Data encoding
Variables
Data
encoding Question Source
Customers’
acceptance and
usage of
innovative
technology (CA)
CA1
I accept using new application in event
practices
Venkatesh, V.,
Morris, M. G., Davis,
G. B., and Davis, F.
D. 2003. “User
Acceptance of
Information
Technology: Toward
a Unified View,” MIS
Quarterly (27:3), pp.
425–478.
CA2
I am willing to change the existing
processes to apply the new in event
practices
CA3
I am willing to use contactless
technologies in event practices
Effort expectancy
(EE)
EE1
I easily understand the utility that the
application provides.
EE2
Learning how to use a new app is easy for
me.
EE3
Overall, Effort expectancy is a factor in
my decision to adopt new technology
Performance
expectancy (PE)
PE1 I would find (found) such a useful app
PE2
The app helped me to keep an eye on my
cost of event
PE3
Overall, Performance expectancy is a
factor in my decision to adopt new
technology
Facilitating FC1 I have several accessories that can install

conditions (FC) apps.
FC2
I understand how to install accessories to
use new technologies
FC3
Overall, Facilitating conditions was a
factor in my decision to use contactless
technologies
Hedonic
motivation (HM
HM1
Using such contactless technology would
be interesting.
HM2
I think the information provided by
contactless technology would be very
interesting.
HM3
Overall, Hedonic motivation is a factor
that helps me use contactless technology
Price value (PV)
PV1
Do you care about the price of the
product when using contactless
technologies
PV2
Do you care about the cost of accessories
when using contactless technologies
PV3
Overall, price value is a factor that helps
me use contactless technologies
Social influence
(SI)
SI1
When I see companies around me
experimenting with contactless
technology, I tend to follow everyone's
lead
SI2
When I see large enterprises adopting
contactless technology, I will use new
products
SI3
Overall, Social influence is a factor that
helps me use contactless technology
3. Methodology
3.1 Identification of paradigm
This study also uses the analytical method in research, which is SPSS (Henseler, Ringle,
& Sinkovics, 2009) which is applied in many marketing studies (McDaniels & Gates, 2015).
SPSS was used to overcome the limitations of the regression method. Developed from

econometric principles and combined with organizational principles of psychology and
sociology, SPSS is seen as the evolution of many models. SPSS has become an integral part of
academic and management research. The approach of SPSS in this study is a reflective
approach, in which the indicators can reflect latent variables (Anderson & Gerbing, 1988).
The independent variables used in this study are: effort life, performance life,
facilitating conditions, hedonic motivation, price value, and social influence. The effort life of
"Low-touch" applications evaluates the application of "low-touch" in events as well as
calculates the performance life of the application. Price also greatly affects the consumption of
low-touch technology and affects society. Because when the price is more reasonable, the
coverage is higher and leads to more people knowing and helping low-touch become familiar.
These variables are independent of each other and change does not depend on the object but
comes from the technology itself. So the customer dependent variable is the only factor
influencing the development of touchless technology. It is the acceptance and use of technology
by customers when low-touch comes in.
3.2 Justification for choice of methodology and methods
In this study, the author uses customers who have participated in outdoor activities,
especially large events with the participation of many people. Among those events was the
application of contactless technology in the field of event organization at the time of the
COVID-19 outbreak. The sampling method in use for this topic. Questionnaires related to
independent or dependent variables all use questions close to the Likert scale 5. Likert scale is
a scale that shows the opinions, attitudes and perceptions of a person or a group of people.
people to some extent about a symptom or phenomenon (Djaali, 2008). This study uses
variables and measures Venkatesh to develop (2003, 2012) performance expectations.
PE1: I find using the "Low-touch" method very helpful in participating in events
PE2: Using the "Low-touch" method helps limit the possibility of disease transmission.
PE3: "Low-touch" increases my event participation.
PE4: "Low-touch" is very easy to use and touch for me
PE5: "Low-touch" makes me feel more comfortable and secure when attending events
Indicators that come from social influence are also scaled Likert scale.
SI1: People I consider important should use "low-touch" means while attending the
event
SI2: Circumstances affecting me when using "Low-touch" to participate in events
SI3: The opinion that the use of "low-touch" is very necessary. Above are some typical
criteria to establish a Likert scale to measure the customer's attitude when using "low-touch".

Reliability testing is an indispensable method when injecting an application into an
external model to ensure proper measurements and analysis are used. Reliability testing can
use declaration methods that are Cronbach's alpha and composite reliability. Cronbach's alpha
measures the lower limit of the confidence value of a building, while composite reliability
measures the actual value of the reliability of a building. An alpha value or composite
confidence higher than 0.7, although a level of 0.6 is still acceptable (Hair et al., 2014). Check
out the model inside. These tests are performed to check the relationship between latent
constructs. There are some internal structural or model tests. a) R Square > 0.67 (strong), 0.33
(moderate), 0.19 (weak) (Abdillah & Jogianto, 2009); b) Path Factor estimation is done by
Bootstrapping procedure; c) The relevance of the prediction (Q Square) also known as Stone-
Geisser's. d). Q Square if the obtained values are 0.02 (small), 0.15 (medium) and 0.35 (large)
(Vincenzo, Chin, Henseler, & Wang, 2010)
Hypothesis testing. To test the hypothesis will be analyzed from the P-value
of the SPSS test. To test this hypothesis, the value of P must be greater than 0,
with significance between 1-95% or 0.05. In the P-value test, to test hypotheses,
it is often used P < 0.05 instead of P ≤ 0.05 (Kock & Hadaya, 2018).
Moderation Test. Moderation calculation using t and P-Value tables to analyze
accommodation by age, sex, and experience to increase or decrease the impact of performance
and effort life, social influence, condition creating conditions, motivation for enjoyment and
habit of paying later (Y). The censorship test will show the role of the variable as pure,
potential, proximate, or predictive censorship. (Hair, Hult, Ringle, & Marko, 2017).
3.3 Limitations of the research design
Measurement models are evaluated based on the reliability of customers when using
low-touch services as well as internal consistency, structure of reliability and validity (Dijkstra
& Henseler, 2015b; Jöreskog , 1971). In addition, the Likert scale also clearly shows the
customer's attitude when experiencing and gives the most objective opinions to evaluate the
development potential of this low-touch model. The internal consistency of the works is
evaluated based on the aggregate reliability. Cronbach's alpha indicates the lower bound by
internal consistency, the composite confidence represents the upper bound, and rho_A lies
between the two, thus giving a good representation of the internal consistency . The metrics
are at a confidence level so this value is recognized and all other constructs are consistent.
Although these methods are analyzed based on the COVID-19 pandemic situation through the

problem of customers using Low-touch, however, even if the pandemic is controlled later, this
model can still thrive after the pandemic.
If in the past low-touch was formed and developed by the mandatory situation of the
pandemic to limit contact, because of its ease of use and popularity, people will continue to use
the software. more low-touch. The effect of effort expectations on technology is not significant
for businesses, especially event companies. That means low-touch makes it more accessible to
customers and easier to use. Although the test results and statistics differ, the traditional method
and the one-touch check-in method are easier for both the event organizer and the customer.
Social influence represents previous behavior. If in the past, face-to-face contact played an
important role in human-to-human communication, now online technologies and methods to
reduce contact are increasingly recommended. As a strong social influence in the decision
making of event organizers as well as customers in the adoption of touchless technologies in
use. The performance of customers as well as organizations is increasingly strong because of
its convenience and simplicity.
When used to using one-touch technologies, customers will feel convenient, even
addicted to using these technologies because of its convenience and essentials. Non-touch
technologies not only limit the possibility of person-to-person contact, but this also reduces the
wait time for customers to check-in when participating in the event as well as the speed of the
joining process when customers can actively check-in early.
Furthermore, in the multi-group analysis, the generation is divided into two categories,
generation Y and generation Z. Millennials or millennials (Gunawan, et.al, 2019) are those
born between 1981 and 1990. 1997, while Gen z was born after 1998. For Generation Y it is
required longevity of effort, hedonic motivation as well as performance lifespan that
significantly influences the transition from old to new. However, Generation Z is very easy to
accept new things, even GenZ is the ones who create new things to contribute to the
development of society. Therefore, it is very easy to accept new things and changes in the
future. Moreover, with the global trend towards technology as well as automation, low-touch
is also an influence from technology. And of course, low-touch is also a strong response of
later society.
4. Findings/Results
4.1 Cronbach’s alpha
Cronbach (1951) gives the reliability coefficient for the scale. Cronbach's Alpha
coefficient best measures the reliability of the scale with 3 or more observed variables. In some
cases, the scale consists of only 2 observed variables, and the reliability can still be measured.

However, this is not recommended with the construction of a scale consisting of only 2
observations, there will be problems with reliability quality when the orientations of these 2
observations are different. Cronbach's Alpha coefficient has a variable value in the interval
[0,1]. In theory, the higher this coefficient, the better (the more reliable the scale is). However,
this is not entirely accurate because Cronbach's Alpha coefficient is too large (about 0.95 or
more) showing that there are many observed variables in the scale that do not differ from each
other, they are almost exactly the same in terms of scale. Meaning, this phenomenon is called
duplication in the scale.
According to Tavakol and Dennick (2011) Cronbach alpha test criteria : If a
measurement variable has the correlation coefficient of the total variable,
Corrected Item – Total Correlation ≥ 0.3, then that variable meets the
requirements. Corrected Item - Total Correlation coefficient represents the
correlation between that observed variable with the rest of the variables in the
scale, if this observed variable has a stronger correlation with the variables in the
group, the better it is. Thus, when performing the Cronbach's Alpha reliability test,
the observed variable has a total correlation coefficient of less than 0.3, it is
necessary to remove that variable and run it again for the second time.
Cronbach’s Alpha coefficient value level:
● From 0.8 to close to 1: the scale is very good.
● From 0.7 to close to 0.8: good usable scale.
● From 0.6 and up: qualifying scale.
According to Taber. (2018) When performing Cronbach's Alpha analysis for a factor,
if the Cronbach's Alpha coefficient of the group is less than 0.6 and no variable in the group
has Cronbach's Alpha if Item Deleted is greater than 0.6, it is necessary to consider removing
the whole factor. In addition, it is also important to pay attention to the value of the column
Cronbach's Alpha if Item Deleted, this column represents the coefficient Cronbach's Alpha if
the type of variable under consideration. Usually we will evaluate together with the correlation
coefficient of the total variable, Corrected Item - Total Correlation, if the Cronbach's Alpha if
Item Deleted value of a variable is greater than the Cronbach's Alpha coefficient of the group,
and the Corrected Item - Total Correlation value is smaller. 0.3 will remove the observed
variable under consideration to increase the reliability of the scale.

Table : Cronbach’s alpha of Customers’ acceptance and usage of innovative
technology
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based
on Standardized Items N of Items
0,911 0,912 3
Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
CA1 7,02 2,753 0,829 0,687 0,867
CA2 6,9 2,602 0,819 0,672 0,874
CA3 6,83 2,542 0,819 0,671 0,875
The variable "Customers’ acceptance and usage of innovative technology" has
Cronbach's alpha value greater than 0.6 and Cronbach's Alpha if Item Deleted value is less than
Cronbach's alpha value, so The variable "Customers’ acceptance and usage of innovative
technology" achieves reliability.
Table 2: Cronbach’s alpha of Effort expectancy
Cronbach's
Alpha
Cronbach's Alpha Based on
Standardized Items N of Items
0,807 0,808 3
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
EE1 7,02 3,251 0,619 0,384 0,776
EE2 7,13 3,253 0,681 0,47 0,71
EE3 7,09 3,334 0,668 0,455 0,724
The variable "Effort expectancy" has Cronbach's alpha value greater than 0.6 and
Cronbach's Alpha if Item Deleted value is less than Cronbach's alpha value, so The variable
"Effort expectancy" achieves reliability.

Table: Cronbach’s alpha of Performance expectancy
Cronbach's
Alpha
0,052 0,053 3
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
PE1 6,65 3,143 0,068 0,01 -,086
PE2 6,5 3,411 0,042 0,012 -,008
PE3 6,64 3,565 -0,03 0,002 0,183
The variable " Performance expectancy" has Cronbach's alpha value less than 0.6, so
The variable "Performance expectancy" is not reliable
Table: Cronbach’s alpha of Facilitating conditions
Cronbach's
Alpha
0,79 0,791 3
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
FC1 7,03 2,73 0,657 0,431 0,689
FC2 6,93 2,588 0,625 0,395 0,722
FC3 6,92 2,742 0,613 0,379 0,734

The variable "Facilitating conditions" has Cronbach's alpha value greater than 0.6 and
"Facilitating conditions" achieves reliability.
Table: Cronbach’s alpha of Hedonic motivation
Cronbach's
Alpha
Cronbach's Alpha Based on Standardized
Items N of Items
0,662 0,663 3
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
HM1 7,1 2,085 0,473 0,227 0,567
HM2 7,14 1,972 0,452 0,205 0,595
HM3 7,26 1,974 0,495 0,247 0,535
The variable "Hedonic motivation" has Cronbach's alpha value greater than 0.6 and
"Hedonic motivation" achieves reliability.
Table: Cronbach’s alpha of Price value
Cronbach's Alphaa
Cronbach's Alpha Based on Standardized
Itemsa N of Items
-0,052 -0,041 3
a The value is negative due to a negative average covariance among items. This violates
reliability model assumptions. You may want to check item codings.
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if
Item
Deleted
PV1 6,69 3,385 -0,084 0,01 0,152

PV2 6,6 3,31 -0,02 0,016 -,046a
PV3 6,74 3,172 0,042 0,007 -,221a
a The value is negative due to a negative average covariance among items. This
violates reliability model assumptions. You may want to check item codings.
The variable " Price value" has Cronbach's alpha value less than 0.6, so The variable
"Price value" is not reliable
Table: Crobach’s alpha of social influence
Cronbach's
Alpha
Cronbach's Alpha Based
on Standardized Items N of Items
0,767 0,767 3
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
SI1 7,11 2,07 0,638 0,419 0,644
SI2 7,22 2,135 0,637 0,417 0,645
SI3 7,11 2,554 0,533 0,284 0,758
The variable "social influence" has Cronbach's alpha value greater than 0.6 and
"social influence" achieves reliability.
In conclusion, in total of 6 initially proposed variables Customers' acceptance and usage
of innovative technology, Effort expectancy, Performance expectancy , Facilitating condition,
Hedonic motivation, Price value, Social influence, there are 4 variables with data that achieve
reliability. Reliability after performing Cronbach alpha test includes: Customers' acceptance
and usage of innovative technology, Effort expectancy, Facilitating condition, Hedonic
motivation, Social influence and Two variables that fail to be reliable are Performance
expectancy and Price value
4.2 EFA
According to DeCoster. (1998). Exploratory Factor Analysis (EFA) is an analysis used
mainly to reduce and summarize data. In scientific research, a research paper can collect a fairly
large number of variables, and most of these variables are related (or correlated) with each
other. Exploratory factor analysis can reduce the number of variables to an appropriate level.

Table: EFA test
KMO and Bartlett's Testa
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. 0,794
Bartlett's Test
of Sphericity
Approx. Chi-Square 837,144
df 66
Sig. 0
a Based on correlations
Rotated Component Matrixa
Raw Component
1 2 3 4
EE1 0,856
EE2 0,875
EE3 0,799
FC1 0,714
FC2 0,758
FC3 0,771
HM1 0,324
HM2 0,317
HM3 0,384
SI1 0,749
SI2 0,739
SI3 0,54
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 4 iterations.
The exploratory factor analysis results show that the independent variables are
classified into 4 different groups according to the original variables. 4 groups include: EE(EE1,
EE2, EE3); FC (FC1;FC2;FC3); HM (HM1, HM2, HM3); SI (SI1, SI2, SI3)
4.3. Regression analysis
Table: Regression results

Variables Entered/Removeda
Model
Variables
Entered
Variables
Removed Method
1 SI, EE, FC, HMb . Enter
a Dependent Variable: CA
b All requested variables entered.
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 ,761a 0,579 0,571 0,51995 2,096
a Predictors: (Constant), SI, EE, FC, HM
b Dependent Variable: CA
Coefficientsa
Model Unstandardized Coefficients
Standardized
Coefficients t Sig.
95,0% Confidence
Interval for B
B
Std.
Error Beta
Lower
Bound
Upper
Bound
1 (Constant) -0,628 0,244 -2,577 0,011 -1,108 -0,148
EE 0,193 0,044 0,21 4,354 0 0,106 0,28
FC 0,292 0,051 0,287 5,704 0 0,191 0,393
HM 0,419 0,063 0,346 6,699 0 0,296 0,542
SI 0,248 0,054 0,222 4,579 0 0,141 0,355
a Dependent Variable: CA
=> Regression model
CA= -0.628 + 0.193*EE + 0.292 * FC +0.419 * HM + 0.248 *SI
R-square
According to Westfall and Arias. (2020) The formula for calculating R-squared
coefficients comes from the idea: the entire variation of the dependent variable is divided into
two parts: the part of variation due to regression and the part of variation due to non-regression.
In which:

● Regression Sum of Squares (RSS): sum of squared deviations explained from
regression
● Residual Sum of Squares (ESS): sum of residual squares deviations
● Total Sum of Squares (TSS): sum of all squared deviations
The R-squared value ranges from 0 to 1. The closer the R-squared is to 1, the more
suitable the built model is to the dataset used to run the regression. The closer R-squared is to
0, the less suitable the built model is for the dataset used for regression. The R-square value of
model 1 is 0.9906 indicating that the independent variables: Effort expectancy, Facilitating
condition, Hedonic motivation, Social influence can explain 57.9% impact on the dependent
variable: Customers’ acceptance and usage of innovative technology
The meaning of Adjusted R-squared is the same as that of R-squared, which reflects the
goodness of fit of the model. The adjusted R-squared calculated from R-squared is more
commonly used because this value more closely reflects the goodness of fit of the multivariable
linear regression model (Westfall and Arias, 2020). The adjusted R-squared does not
necessarily increase as we add more independent variables to the model. The model's adjusted
R-squared value is 0.571, showing that the independent variables can explain 57.1% of the
impact on the dependent variable.
Model F-test: A ratio that represents the change between the mean and the variation of
the samples is called the F-test. This index is used to check if the model has an independent
variable that can be influenced by the dependent variable. Hypothesis:
Ho: b1 = b2 = b3 = b4 = 0
H1: bj # 0
According to the ANOVA table, the Sig value of the F test is 0.000, this value is less
than significance level 0.05.. Therefore, H0 is rejected and Ha is accepted. Thus, the model
exists at least one variable that can affect Customers’ acceptance and usage of innovative
technology
Model T-test: T-test is used to test whether each independent variable can affect the
dependent variable or not. Hypothesis:
Ho: bj = 0
H1: bj # 0
Based on the table of regression results, the variables: Effort expectancy, Facilitating
condition, Hedonic motivation, Social influence have Sig value less than 0.05, showing that
these variables are statistically significant in explaining the effect of the dependent variable.

The coefficient of EE variable is 0.193, showing that EE has a positive impact on
Customers’ acceptance and usage of innovative technology. When EE increases by 1 unit,
Customers’ acceptance and usage of innovative technology will increase to 0.193 units
The coefficient of FC variable is 0.292, showing that FC has a positive impact on
Customers’ acceptance and usage of innovative technology. When FC increases by 1 unit,
The coefficient of HM variable is 0.419, showing that HM has a positive impact on
Customers’ acceptance and usage of innovative technology. When HM increases by 1 unit,
The coefficient of SI variable is 0.248, showing that SI has a positive impact on
Customers’ acceptance and usage of innovative technology. When SI increases by 1 unit,
5. Conclusion
5.1 Summary of what you found out in relation to each research question you
investigated Your contribution to the existing body of knowledge on the chosen business
issue
The explosive trend of digital technology has given rise to many new economic models
such as circular economy, sharing economy, creative economy... Especially, the outbreak of
the COVID-19 pandemic has , is and will affect not only human health but also all activities of
working, living, eating, resting, shopping, exercising and using free time on a global scale. .
The longer the pandemic lasts, the longer the epidemic prevention measures are applied, the
more likely people are to form new habits that disrupt the economy. The coming years will be
shaped by digital technology trends and the current crisis. According to a scenario of the Board
of Innovation, it will take another 18-24 months for the world to return to "normal" when
policies on hygiene and prevention of epidemics, social distancing, travel restrictions, bans on
gatherings episode... was gradually removed. That's why the concept of "Contactless
Economy" or "Less Touch Economy" appeared to refer to the tendency of consumers and
businesses to adapt to the new context. The application of contactless technologies in event
practices is very important for the growth of the business. Research shows that four factors
positively influence applying contactless technologies in event practices during covid-19
pandemic towards customer attitudes including: Effort expectancy, Facil condition, Hedonic
motivation, Social influence. Thus, to be able to successfully apply contactless technologies
and bring in revenue and profit for businesses, the author needs to focus on the four factors
above.

According to Tran Van (2021), the "contactless economy" still faces many challenges.
The legal corridor for the "contactless economy" has not had significant breakthroughs, has not
been legislated and has not kept up with the development of the market. In addition, the
infrastructure and technical equipment serving the "contactless economy" have not yet met the
requirements of consumers... In the coming time, to promote the "contactless economy"
development, it is necessary to focus on implementing the following contents:
On the side of state agencies
● Completing the legal corridor, creating a basis for the "contactless economy"
model to develop in the right direction, overcoming the situation that legal regulations do not
keep up with the development reality of science and technology. science - technology.
● Continue to improve the law on innovative start-ups, intellectual property, trade,
investment and business to create favorable conditions for the process of national digital
transformation and the development of products and services. new economic model based on
digital technology, internet and cyberspace...
● Research and promulgate a system of national standards and regulations as a
foundation for the application and development of core technologies of the contactless
economy in order to create synchronization and a legal framework for research and
development. new technologies.
For the business community
● Pioneering in building a contactless economic model, focusing on investing in
promoting e-commerce, artificial intelligence... development because, after all, businesses are
the beneficiaries. from this economic model.
● Focus on developing high-tech human resources to serve the operation of new
business models in the contactless economy.
5.2 Limitations of research and suggestions for future research
The study determines the influence of the variables Effort expectancy, Performance
expectancy, Facilitating condition, Hedonic motivation, Price value, Social influence on
Customers' acceptance and usage of innovative technology. The research results have shown
that four variables are statistically significant, but there are still some limitations: Firstly, the
R-square value of the model is only 57.9%, this is an acceptable level but not yet an acceptable
level. can confirm with certainty the significance of the statistical model. Second, the size of
the study is 220, this is a relatively small number, there are not many companies applying
contactless technologies in Vietnam. Third, the data source is collected from interviews with
businesses, so the information provided may not be complete and accurate. In addition,

enterprises do not yet trust the results of scientific research of students, so they have not taken
the necessary actions to support. Differences in data from different sources make the processing
of these data not comprehensive or efficient.
5.3 Implications of your research for practice
The new technology trends of the world are dominating the events industry is a thing
that has been confirmed by many studies. These technologies are helping event planners and
the attendee experience is also enhanced. The Covid 19 pandemic has forced many planners to
turn their in-person events into indirect meetings. Many emerging event technologies have
made these moves possible, and it is likely that they will persist long after this health crisis is
over. Therefore, in order to really put the contactless technology platform into practice, a full
evaluation and research process is needed; customer-related issues, such as the attitudes and
acceptability of these applications. Basically, this study shows that the customer's attitude is
quite positive and eager to use this application during the Covid 19 period. Although there are
new things that customers need to learn, customers often show a positive attitude after a period
of experience with the actual event organization application.
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Appendix
Questionnaire:
Customers’
acceptance
and usage of
innovative
technology
CA1 I accept using new application in event practices
CA2
I am willing to change the existing processes to
apply the new in event practices
CA3 I am willing to use contactless technologies in event

practices
Effort
expectancy
EE1
I easily understand the utility that the application
provides.
EE2 Learning how to use a new app is easy for me.
EE3
Overall, Effort expectancy is a factor in my decision
to adopt new technology
Performance
expectancy
PE1 I would find (found) such a useful app
PE2
The app helped me to keep an eye on my cost of
event
PE3
Overall, Performance expectancy is a factor in my
decision to adopt new technology
Facilitating
conditions
FC1 I have several accessories that can install apps.
FC2
I understand how to install accessories to use new
technologies
FC3
Overall, Facilitating conditions was a factor in my
decision to use contactless technologies
Hedonic
motivation
HM1
Using such contactless technology would be
interesting.
HM2
I think the information provided by contactless
technology would be very interesting.
HM3
Overall, Hedonic motivation is a factor that helps me
use contactless technology
Price value
PV1
Do you care about the price of the product when
using contactless technologies
PV2
Do you care about the cost of accessories when using
contactless technologies
PV3
Overall, price value is a factor that helps me use
contactless technologies
Social
influence
SI1
When I see companies around me experimenting
with contactless technology, I tend to follow
everyone's lead
SI2
When I see large enterprises adopting contactless
technology, I will use new products

SI3
Overall, Social influence is a factor that helps me use
contactless technology

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