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Royal Holloway University of London
2015/2016
The acceptance of Near Field Communication technology among millennial social media users.
Domenic Boni
Student ID: 100832118
Word Count: 10 066
9th May 2016
2
Independent Research Project Declaration Form PRE-MASTERS DIPLOMA FOR INTERNATIONAL STUDENTS INDEPENDENT RESEARCH PROJECT (FINAL DRAFT) Declaration to be signed by the student: I have read the following guidelines on plagiarism and declare that all work submitted is my own and that full reference has been made to other material used. “All work submitted by students as part of the requirements for any examination or other assessment must be expressed in their own words and incorporate their own ideas and judgments. Plagiarism - that is the presentation of another person’s thoughts or words as though they were one’s own - must be avoided, with particular care in coursework and essays and reports written in students’ own time. Deliberate plagiarism in coursework is as serious as deliberate cheating in an examination. Direct quotations from the published or unpublished work of others must always be clearly identified as such by being placed inside quotation marks, and a full reference to their source must be provided in the proper form. A series of short quotations from several different sources, if not clearly identified as such, constitutes plagiarism just as much as does a single unacknowledged long quotation from a single source. Equally, if a student includes a summary of another person’s ideas or judgments the source must be acknowledged and the work referred to included in the bibliography. Failure to observe these rules may result in an allegation of cheating. Students should therefore consult their Personal Tutor, Personal Adviser or Course Director if they are in any doubt about what is permissible.” Student’s signature: Domenic Boni ………………………………….……………………………… Date: 9 May 2016……………………………………………………………………………………
Submission to IN002 Signature of member of staff …………………………………………………………………
Date: ………………………………………………………………………… Time: …………………………………….…………………………………………..
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Abstract
Near Field Communication (NFC) is a short range, wireless data transfer technology
able to interact and communicate even in the absence of an Internet connection. The
technology has grown rapidly since its inception less than a decade ago, bringing
with it new opportunities for innovative mobile applications and services. In order to
keep up with the pace of the growth of mobile devices with NFC capability, it is
imperative for both academics and processionals to understand the factors
influencing the acceptance of this technology. Therefore, this study set out to
discover how millennials perceived NFC technology in a social media contact
sharing capacity.
Drawing from secondary research and utilizing the Unified Theory of Acceptance and
Use of Technology (UTAUT) and the Technology Acceptance Model (TAM), a new
conceptual framework was created. Key factors influencing the attitude millennials
form when accepting NFC were tested. Compatibility and Perceived Usefulness
were the most influential on attitude formation followed closely by Social Influence.
Perceived Risk appeared to have no significant influence over the formation of
attitudes towards NFC for social media contact sharing. Furthermore, the results
identified there being a significant positive relationship between attitude formed and
behavioural intention to adopt NFC in a social media environment.
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This research has successfully contributed to filling a prior knowledge gap in
academic research and has the ability of facilitating marketers of NFC services to
successfully reach millennial consumers.
Keywords: Innovative Technology – Technology Acceptance – Behavioural
Intention – Millennial - NFC
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Acknowledgements I would like to thank my personal tutor Laryssa Whittaker and academic supervisor
Chloe Preece for the support and feedback they have both given me throughout the
duration of this research, without them none of this would have been possible. Thank
you for helping me pursue research in an area I am passionate about and thank you
for the endless guidance in helping me make this paper something I am truly proud
of.
Declaration Abstract………………………………………………………………………………………i Acknowledgements………………………………………………………………………..ii List of Appendices ........................................................................................................ 1 List of Tables ................................................................................................................. 1 List of Figures ................................................................................................................ 2 Chapter 1: Introduction ................................................................................................ 3 1.1) Dissertation Outline ................................................................................................................................................ 6 Chapter 2: Literature Review ....................................................................................... 7 2.1) Millennials .................................................................................................................................................................... 7 2.2) Social Media ............................................................................................................................................................ 10 2.3) Near Field Communication .............................................................................................................................. 13 2.3.1) Tag Reader / Writer ........................................................................................................................................ 14 2.3.2) Peer-to-Peer ....................................................................................................................................................... 15 2.3.3) Card Emulation ................................................................................................................................................. 17
2.4) UTAUT/TAM Models ........................................................................................................................................... 19 2.5) Conceptual Model and Hypotheses ............................................................................................................ 23 2.5.1) Hypotheses ......................................................................................................................................................... 24
2.6) Conclusion ................................................................................................................................................................ 26 Chapter 3: Methodology ............................................................................................. 28 3.1) Introduction .............................................................................................................................................................. 28 3.2) Research Methodology ...................................................................................................................................... 28 3.3) Research Design .................................................................................................................................................. 31 3.4) Data Collection ....................................................................................................................................................... 32 3.4.1) Secondary Data ................................................................................................................................................ 32 3.4.2) Primary Data ....................................................................................................................................................... 32
3.5) Questionnaire Design ......................................................................................................................................... 33 3.6) Data Analysis .......................................................................................................................................................... 35 3.7) Validity ........................................................................................................................................................................ 36 3.8) Ethical Considerations ....................................................................................................................................... 37 Chapter 4: Findings .................................................................................................... 38 4.1) Demographics ........................................................................................................................................................ 38 4.1.1) Age ........................................................................................................................................................................... 38 4.1.2) Gender ................................................................................................................................................................... 39 4.1.3) Smartphone ownership ................................................................................................................................ 40 4.1.4) Experience with NFC technology ........................................................................................................... 41
4.2) Reliability Testing .................................................................................................................................................. 42 4.3) Descriptive Statistics ........................................................................................................................................... 43 4.3.1) Perceived Usefulness ................................................................................................................................... 45 4.3.2) Perceived Ease of Use ................................................................................................................................. 46 4.3.3) Social Influence ................................................................................................................................................ 47 4.3.4) Compatibility ....................................................................................................................................................... 48 4.3.5) Perceived Risk .................................................................................................................................................. 49 4.3.6) Attitude towards Use ..................................................................................................................................... 50 4.3.7) Behavioural Intention ..................................................................................................................................... 51
4.4) Hypothesis Testing and Regression Analysis ....................................................................................... 52 4.4.1) Hypothesis Testing ......................................................................................................................................... 52 4.4.2) Regression Analysis ...................................................................................................................................... 57
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Chapter 5: Discussion of Findings ........................................................................... 60 5.1) Social Influence and Perceived Ease of Use ......................................................................................... 60 5.2) Compatibility and Perceived Usefulness .................................................................................................. 61 5.3) Perceived Risk ....................................................................................................................................................... 61 5.4) Attitude Toward Use and Behavioural Intention to Adopt ............................................................... 63 Chapter 6: Conclusion ................................................................................................ 65 6.1) Contribution ............................................................................................................................................................. 65 6.1.1 Academic Contribution ................................................................................................................................... 65 6.1.2 Applied Contribution ........................................................................................................................................ 66
6.2) Limitations and Future Research Direction ............................................................................................. 66 References ................................................................................................................... 68
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List of Appendices
1. Appendix 1 – Online Questionnaire
2. Appendix 2 – Hypothesis Testing
3. Appendix 3 – Regression Analysis
4. Appendix 4 – Ethics Code Certificate
List of Tables 1. Reliability Test
2. Descriptive Statistics - Perceived Usefulness
3. Descriptive Statistics - Perceived Ease of Use
4. Descriptive Statistics - Social Influence
5. Descriptive Statistics - Compatibility
6. Descriptive Statistics - Risk
7. Descriptive Statistics - Attitude Towards Use
8. Descriptive Statistics - Behaviour Intention
9. Hypothesis Testing
10. Regression Analysis – Model Summary
11. Regression Analysis – Significance Testing (ANOVA)
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List of Figures 1. Dissertation Outline
2. NFC Operation Modes
3. Technology Acceptance Model
4. Unified Theory of Acceptance and Use of Technology – Constructs
5. Unified Theory of Acceptance and Use of Technology – Model
6. Conceptual Model
7. Deduction and Induction
8. Age Demographics
9. Gender Demographics
10. Smartphone Type
11. Experience NFC
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Chapter 1: Introduction
For some time, experts and researchers have studied the possible benefits of
linking the virtual world of the Internet with a physical one. Since the
introduction of Near Field Communication (NFC) technology, the idea of a link
between these two worlds is fast becoming a ubiquitous reality.
NFC is a short-range wireless technology, already very common in
smartphones globally (Want, 2011). The NFC chip inside a device
communicates with other NFC ready enabled devices, ranging from transport
systems, ticketing procedures through to seamless and efficient payments.
The technology has grown in popularity since the formation of the NFC Forum
in 2004. According to IHS Technology (NYSE: IHS) by 2018, 1.2 billion
mobile devices will contain NFC chips, igniting a new wave of potential
applications introduced to compliment this technology.
There are approximately 2 billion Internet users on social networking
platforms. This number is growing rapidly due to increased mobile device
usage;; mobile social media is at the forefront of technological advancement
(Leading global social networks 2016 | Statistic, no date). Twenge (2009)
highlights the importance of understanding the millennial generation when
considering innovative technology adoption due to their increasingly different
traits compared to their older counterparts, Generation X.
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Considering the staggering amount of mobile social media usage, millennials
are increasingly demanding ecosystems that are more compatible with their
digital lives (Twenge 2009).
It has become apparent in reviewing secondary research that the majority of
academic and applied focus in the recent past has been placed on NFC
technology for contactless payment services. Research conducted by Dutot,
(2015), Pham and Ho, (2015), Chen and Chang, (2013) have all focused on
user behaviour and attitudes towards adoption of NFC mobile payments.
While this research offered excellent grounding for this study, Hongwei Du
(2013) introduces the idea of peer-to-peer data sharing via NFC enabled
mobile devices, and briefly touches on the impact this technology can have on
social media ecosystems. Minimal research has been conducted on this area
of NFC technology. With a rapidly growing number of NFC enabled mobile
devices coming to market and considering mobile devices are at the forefront
of social media usage, more research concerning peer-to-peer functionality
for NFC needs to be conducted. Additionally, with no emphasis whatsoever
on millennial adoption patterns of this innovative technology, this research will
contribute to the gap in academic and applied knowledge.
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The aim of this research was to uncover how millennials perceive NFC
technology for social media contact sharing purposes. The research set out to
devise a framework, which will capture the most important factors that
influence millennials’ attitudes towards the use of the technology in their social
media environment. Furthermore, the result of the attitude formed was then
measured against the behavioural intention to adopt the technology.
This study revised previous secondary literature in the field of technology
adoption and NFC technology, combined with an online questionnaire for
primary data in the quantitative research adopted in this page. The study
aimed to:
1) Understand the degree of influence, Perceived Ease of Use, Perceived
Usefulness, Social Influence, Compatibility and Perceived Risk had on
the attitudes millennials formed towards the use of NFC for social
media purposes.
2) Understand if there was a relationship between the attitude towards the
use of NFC formed by millennials and their behavioural intention to
adopt the technology for social media contact sharing.
Given the lack of knowledge in this subject area, this research was conducted
to offer professionals and marketers of NFC technology additional information
when dealing with millennial consumers.
6
1.1) Dissertation Outline
Figure 1: Dissertation Outline
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Chapter 2: Literature Review This research will attempt to uncover the millennial generation’s technology
acceptance habits looking specifically at Near Field Communication
Technology (NFC) in a social media environment. The literature below
highlights important prior research conducted in the area of Millennials, Social
Media and Near Field Communication technology. Finally, this chapter looks
at various relevant behaviour models previously used to understand user
adoption and acceptance of the technology. A conceptual framework is then
derived from two relevant models to further the study of millennials’ attitudes
and behaviours when accepting or rejecting the technology.
2.1) Millennials
“Born between roughly 1982 and 2002, millennials are the first generation to
grow up with cell phones, personal computers, camcorders, digital music
players, and the World Wide Web” (Schwalbe, p1. 2009). Although there are
no definitive dates to determine millennials, it is widely agreed that millennials
or Generation-Y are those born following Generation X. For the purpose of
this research and due to ethical age considerations, I have defined millennials
as being between the ages of 18-30 years old.
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Marc Prensky (2001), in his article on United States education standards,
expands on the impact the “internet generation” or “Digital Natives”, have on
the current state of not only education but the progression of the world
compared to their older counterparts or “Digital Immigrants” (p.1). The need to
understand the millennial generation and their behaviour towards the use of
digital media and technology has ignited vast academic and business interest.
However, in their book “Millennials Rising: The next generation” Howe and
Strauss (2000, cited in Schwalbe, 2009, p 54) dedicate only one paragraph to
millennials’ use of digital media. Furthermore, 2007 Pew Internet & American
Life Project survey results categorised Americans into types of technology
users, but failed to differentiate between university-aged students and other
adults, as noted by Horrigan (2007, quoted in Schwalbe, 2009, p 54). While
much attention has been given to the millennial generation, there is a lack of
literature in technology adoption attitudes and behaviours of this generation.
This is where this study will look to fill that gap.
Although the above-mentioned research offers valuable information about
millennials, this research will attempt to understand millennials' technology
acceptance habits further by contributing to an area other than educational
settings. This lack of literature on behaviour is reflected in the work of Prensky
(2001) in thinking millennials are always connected and therefore accepting
technology is a phenomenon so deeply engrained in the generation that a
study on the matter would render predictable results.
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Schwalbe (2009) attempts to understand millennials’ digital media usage and
uncovers detailed statistics concerning the generation’s habits. This research
will look to discover what influences millennials’ attitudes when accepting new
technology.
According to Fromm et al. (2011) millennials are 2.5 times more likely to be
early adopters of new technology than any other generation. Furthermore, the
writers contend that, once new technology is introduced, millennials are more
inclined to seek peer affirmation and advice about new technology
advancements from social influences rather than from the companies or
organisations releasing the products. Social affirmation for the millennial
generation is one of the most important influencers in millennial technology
acceptance habits and this study will look to expand on this.
Once they’ve done their research — which includes consulting with
friends and family for advice, both in person and through texting and
social sites — they have a high degree of confidence in the decisions
they’ve made. This may seem contradictory, but it describes how many
Millennials behave. - Fromm et al. (2011)
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2.2) Social Media
Social media platforms allow Internet users to communicate, connect and
interact with new or mutual friends through social networking sites (SNS) and
instant messages (Correa et al., 2010). For the purpose of this study, social
media refers to Social Networking Sites (SNS), which in reality is only one
channel of social media. The reason for narrowing down this definition is that
for the purpose of this study, acceptance of NFC technology will be explored
concerning peer-to-peer contact sharing of social networking sites such as
Facebook, Twitter, Instagram and LinkedIn. Kietzmann, et al., (p 241. 2011)
provide a deeper definition of Social Media by emphasising the fact that these
media platforms are powering the world into a “new communications
landscape”, where users and communities amplify user-generated content in
real time. Ninety percent of users on social networking sites use the platforms
as a means of remaining in touch with their personal contact lists (Lenhart et
al., 2009). The author highlights that three-quarters of users on social
networking sites are under the age of 25. Furthermore, Raacke & Bonds-
Raacke’s (2008) research revealed that one-third of young adults was
checking their profile pages daily with time spent on SNS ranging from one to
three hours. This suggests that further research needs to be conducted in
this area.
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In an interview with wire.com, Mark Zuckerberg, regarded as one of the
“founding fathers” of social media highlights the importance of social media in
today's world by comparing individual social networking sites to that of
companies trying to build a brand for themselves “…It is almost a
disadvantage if you’re not on it now” (Vogelstein, p2, 2009). In their research
on the impact that social media may have on educational transformation,
Davis, et al. (2015), assert that social media enhances the process of
transformation of human relationships and connections, and alters the manner
in which humans “think, organise and act politically” (p. 410).
Kaplan (2012) introduces the concept of mobile social media as a group of
mobile applications that allow the “creation and exchange of user-generated
content” (p. 131). The writer explains the process in which information is
transferred between 1) the sender sharing information and 2) the receiver,
which listens to the information. When investigating the impact mobile devices
play in today’s social communication landscape, understanding the origins of
mobile social media communications will inform this research. For example, a
study conducted by Iwatani and Reuters, (1998, cited in Humphreys, 2013,
pp. 21-22) discusses a product named the “Lovegety”. This device facilitated
the communication between two of the same products within a 5m radius, with
pre-set functions of “let’s chat”, “let’s karaoke” or “get2” (p. 21). When
encountering another device, the product flashed to indicate a match made.
The Lovegety introduced two basic forms of communication.
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Firstly, identification of a new user and secondly the information regarding the
type of social interaction the user was searching for.
An interesting part of the Lovegety research was the consumer’s attitude
towards the adoption of the new technology at the time. The Japanese
adoption of the new technology was as a result of social influence by their
peers and family members (p. 22). With this early understanding of social
interaction technology, social influence in the acceptance of new technologies
deserves further research. Studies such as Li (pp. 265-266, 2013) on social
influence distinguish between ‘informational social influence’ and ‘normative
social influence.’ The former is where users accept information from social
groups on the premise of experience, to make informed, quality decisions.
The latter is where social influence pressures users to conform by accepting.
As moderate research has been conducted in this area, more research into
the impact social influence has on millennials is warranted.
It is important to understand the paradigm shift from desktop social media
usage to mobile social media. According to Cortesi et al., (2013)
approximately 100% of teens in Western Europe, Northern America and Asia-
Pacific own a mobile phone, with a high percentage of these being
smartphones. These staggering statistics underscore the shift to increase
mobile social media usage.
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2.3) Near Field Communication
Near Field Communication (NFC) is a variation of Radio Frequency
Identification communication technology. NFC has been widely applauded for
its “hassle-free” stance in communication technology (Chang & Chen 2011).
With its ability to assure user-friendly (no discovery, no pairing as experienced
in Bluetooth) short distance (up to 10cm) wireless communication between
two devices, NFC technology has numerous benefits for both individuals and
industry use (Dutot 2015). Kantner et al. (2008) highlight the key benefit of
NFC is its simplicity of use. A users pre-empted feelings or attitude towards
new technology, positive or negative, according to Holloway et al. (2005) will
be key indicators to the extent to which a user is willing to engage with new
technology. Taylor and Todd (1995) state that users are more ready to accept
a new phenomenon if it is perceived to add more benefit to an older model or
version of the technology. While outside influences are important to
acceptance behaviour, a user’s personal experience is as valuable in forming
an attitude towards a new technology (Petty et al. 1983). Building on the
theory of simplicity, Kantner et al. (2008) highlight the added benefits the
technology offers mobile device users, citing the example of the most
commonly used area of the technology today- contactless payments.
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Also, Csapodi & Nagy, (2007) discuss the further benefits of NFC’s use by
highlighting the sensitivity of energy consumption and state that the
technology may be powered by only one of the two devices in the
communication mode, adding to the sophistication of the technology.
Figure 2: NFC Operation Modes (Source: nfc-forum.org ‘What It Does’, no date)
2.3.1) Tag Reader / Writer
According to the NFC Forum (nfc-forum.org: ‘What It Does’, no date), the
reading and writing functionality of NFC-enabled devices “connects the world
of apps with the physical world”. An NFC device will be able to read
information stored on multiple platforms where another NFC tag exists. In his
study of NFC, Du (2013) discusses the impact the technology is already
having on transportation globally. Simplifying transport logistics and allowing
NFC-enabled users to use their mobile devices to gain further information
about their journey by “smart advertisements”.
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Commuters can hold up their phone to a “smart poster” and instantaneously
communicate with the NFC enabled tag to gain further transport information.
Expanding on Tag Reading and Writing, Du (2013) cites examples of NFC-
enabled devices replacing a hotel room key by the use of a mobile device.
Building on Du (2013) discussion, Roy Want of Google (2011) furthermore
points to the benefits of NFC’s ability of simplifying and transforming boarding
procedures in public transport by the simple tap of an NFC-enabled device.
The author introduces the topic of gaining virtual store coupons by a simple
swipe of the phone and eradicating out-dated methods of collecting stamps in
a paper orientated loyalty card.
2.3.2) Peer-to-Peer
The nature of NFC peer-to-peer communication is similar to Tag Reading and
Writing specifications in that an NFC-enabled mobile device will interact with
another device in the same way it does with, for example, a smart poster,
(nfc-forum.org: ‘What It Does’, no date). Considering the simple nature of the
transfer of information, peer-to-peer NFC communication is highly attractive to
individual users and businesses alike (Want, p.5. 2011). With the ability to
initiate a “viral transfer of information” (Clark, 2011, no pagination) an NFC-
enabled mobile device can share information already acquired from a smart
poster to another NFC-enabled mobile device instantaneously.
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Movie trailers, coupons and games are a few of the endless opportunities for
marketers to penetrate an audience via viral communication and seed
consumers in allowing them to initiate the further communication of
information. Du (2013) introduces the topic of contact sharing and social
media complementing the use of NFC for instantaneous contact sharing
across platforms. Furthermore, an increase in the use of “check-ins” again
benefits the individual user and businesses.
Looking further into mobile commerce, in 2011 PayPal introduced the ability to
include person-to-person transactions (PayPal United Kingdom: Pay, Send
Money & Accept Payments, no date). For the purpose of this study, user
attitudes to NFC will be considered and analysed. At the same time,
perceived risk and security related issues would be a primary consideration
when new users look to adopt this technology. The NFCforum.org offers
various scenarios of possible ‘cybercrimes’ through NFC technology;; one
significant concern is ‘data corruption or modification’ (Security Concerns with
NFC Technology -NearFieldCommunication.org, no date). This research
attempts to understand the variables affecting millennials acceptance of NFC
technology of social media use. Taking this into consideration, it is important
to realise the perceived risks of using this technology that impacts the
attitudes of users in the acceptance process. Determining if millennials
perceive NFC as a threat to their personal information will form part of this
study.
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2.3.3) Card Emulation
NFC-enabled mobile devices also take the form of moving smartcards, (nfc-
forum.org: ‘What It Does’, no date). By just tapping an NFC mobile device
against an NFC terminal, a user can make unlimited small amount purchases
without the use of their credit cards. The benefits for business as stated by Du
(2013) will be the satisfaction the customer feels because of the simplicity of
the transaction. At the same time, the information the merchant receives
about buying habits and preferences will be useful for marketing purposes.
In 2012, global payment transactions accounted for over 15,3% of all
transactions and estimates suggest that by the year 2016 this figure will rise
to over 40.8% according to Portio Research (2012, quoted in Liébana-
Cabanillas et al., 2015, p.2). The most important element of NFC-enabled
mobile devices for payment is the security factor involved with transactions as
agreed by Liébana-Cabanillas et al. (2015), Du (2013) and Want (2011).
Csapodi & Nagy (2007) highlight the users deliberate intent to conduct a
transaction as a justification for security. The implication of the anxiety a user
feels of not being able to physically control the exchange of funds (i.e., with a
pin code or some form of verification) is an important factor for further
research (Chen and Chang 2011). The risk associated with the use of non-
traditional monetary payments has been contentious for many years. The
reliance on the Internet, as well as new forms of payment for goods and
services has brought with it a change in consumer attitudes in the adoption or
acceptance of new technologies.
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Risk is a major influencer of consumer attitudes, which in turn affect the
consumer’s engagement levels (Taylor and Todd, 1995). According to
Forsythe et al. (2006), many innovative technologies have been hindered by
the perceived risk a given technology or service brings. For example, two of
the main concerns is identity theft and credit card fraud. Dutot (2015) explains
the lack of physical contact concerning payments with ‘online’ services to be
an influencer in consumer’s decisions to accept or reject new technology like
NFC. As mentioned above, the lack of physical control (i.e., pin code)
heightens the distrust of consumers because of a fear of transactions being
intercepted and fraud or cybercrime being initiated. These perceived risks
concerning NFC contactless payments will be used in this NFC for social
media contact sharing research and adapted accordingly.
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2.4) UTAUT/TAM Models
With the landscape of information system technology always changing, users’
acceptance of new technology is of utmost importance to technology
manufacturers, corporations and even individual users. Numerous studies on
user behaviour have been carried out to gauge the manner in which people
perceive new technologies. The most common model used in the study of
acceptance of technology is the Technology Acceptance Model (TAM)
constructed by Davis in 1989. It is considered to be one of the most impactful
and relevant research tools of technology acceptance (Tan et al... 2012,
quoted in Dutot, 2015, p 47). Offering two distinct elements influencing
acceptance, namely perceived ease of use and perceived usefulness, the
model presents a very simplified method to understand user’s acceptance of
new technology.
Figure 3: Technology Acceptance Model (Source: Davis 1989)
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Davis (1989) in his design of the TAM, proposed “Perceived Usefulness” (the
extent to which a user finds an application or technology useful) to be directly
affected by “Perceived Ease of Use”. The author believed that even if a user
viewed an application or technology as useful, the perception of the difficulty
to manipulate the application or technology was more important when forming
an attitude. Considering this study is focused on millennials, throughout their
lives, according to Prensky (pp. 1-3. 2001), they have become more
susceptible to adopting new technology, therefore, rendering this relationship
by Davis (1989) less impactful to these “Digital Natives”. Although the
relationship between these two variables will not be discussed in this study,
the variables independent of one another are still of great importance to the
study at hand. The extensive use of this model has been adopted in research
in the field of Information Technology and Information Systems due to its ease
of use (Rupanjali et al., 2013, quoted in Dutot, 2015, p. 46).
With the limitation of this model hindering deeper knowledge of the
acceptance of technology, further research conducted by Venkatesh, Morris,
Davis, and Davis (2003) was carried out to uncover additional variables and
behaviour theories affecting a user's attitude towards acceptance.
A new concept was introduced by the authors, namely The Unified Theory Of
Acceptance And Use Of Technology (UTAUT) model to explain users’
behavioural intention of information technology (Chen & Chang 2011).
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Accounting for constructs across nine critical theories, the UTAUT model
offers a more efficient framework, with a 70% explanatory power, more so
than any other integrated method to date (Venkatesh et al., 2003).
The UTAUT includes constructs from (In chronological order);;
1) Theory of reasoned action (TRA) (Fishbein & Ajzen 1967)
2) Technology Acceptance Model (TAM) (Davis 1989)
3) Model of PC Utilisation (MPCU) (Thompson et al. 1991)
4) Theory of Planned Behaviour (Ajzen 1991)
5) Combined TAM & TPB (C-TAM-TPB) (Taylor and Todd 1995)
6) Innovation Diffusion Theory (IDT) (Rogers 1995)
7) Social Cognitive Theory (SCT) (Compeau and Higgins 1995)
8) Motivational Model (MM) (Vallerand 1997)
9) TAM2 (Vankatesh & Davis 2000)
Combining these nine models indicates a user's attitude towards acceptance,
as well as the intention to use technology.
Upon testing each of the nine above mentioned theories, Venkatesh et al.
(2003) extracted the four key constructs best explaining behavioural intentions
and usage behaviour.
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Figure 4: Four constructs of the UTAUT Model (Source: Venkatesh et al., 2003)
Figure 5: UTAUT Model (Source: Venkatesh et al., 2003)
23
2.5) Conceptual Model and Hypotheses
The above-reviewed literature shows that Social Influence (SI), Perceived
Usefulness (PU), Perceived Ease of Use (PEU), Compatibility (Com) and
Perceived Risk (Risk) are all factors that influence the preconceived attitudes
when millennials accept new technology. This research paper will combine
the UTAUT model (Venkatesh et al., 2003) and the TAM (Davis, 1989) to
construct a research questionnaire that was designed to investigate the
constructs influencing attitude towards use and behavioural intention to adopt
NFC. While there has been a moderate amount of research conducted on the
adoption of NFC for mobile payment services with the use of mobile devices
(Dutot 2015, Chen and Chang 2013), research into millennials’ attitudes and
acceptance of NFC has yet to be uncovered.
Figure 6: Proposed Conceptual Model (Source: own contribution)
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2.5.1) Hypotheses
By forming the six hypotheses below and using secondary data provided
mainly by Chen & Chang (2013);; Dutot, (2015);; Pham & Ho (2015) (among
others) I have also used my experience as a millennial technology user. By
combining the previous research with real life experience with NFC
technology and social media, the following hypotheses were formed and will
be tested in chapter 4.
The hypotheses are as follows:
H1: There is a positive relationship between Attitude towards the use of NFC
and the Social Influence experienced by a millennial user.
H2: There is a positive relationship between Attitude towards the use of NFC
and the perceived usefulness of the technology by a millennial user.
H3: There is a positive relationship between Attitude towards the use of NFC
and the perceived ease of use of the technology by a millennial user.
H4: There is a positive relationship between Attitude towards the use of NFC
and the compatibility in a millennial user's lifestyle.
25
H5: There is a negative relationship between Attitude towards the use of NFC
and the risk associated with the technology experienced by a millennial user.
H6: Millennial Social Media user’s attitude towards NFC has a significant
positive relationship with the user’s behavioural intention to use the
technology.
The proposed research model includes the variables of Gender, Age and
Experience using NFC as moderators of the user’s behavioural intention
(Chen and Chang, 2011).
26
2.6) Conclusion
The chapter above offers detailed research on previous literature of the
millennial generation, Social Media, NFC and also previously investigated
models presenting methods to uncover user attitudes and adoption behaviour
of new technologies.
The literature demonstrates factors needed to study and understand user’s
attitude about technology. This includes Social Influences, Perceived ease of
use and usefulness of the technology, Compatibility of the technology to the
lifestyle of the user, as well as the risk factors involved when forming
preconceived attitudes towards technology adoption. Through a detailed
review of technology acceptance models, it was concluded that the two most
suitable models in drawing up the framework for this study were the UTAUT
(Venkatesh et al., 2003) and the TAM (Davis, 1989). The studies of Chen &
Chang, (2013), Dutot, (2015) and Pham and Ho (2015) on the adoption of
NFC technology with mobile payments gave valuable insight into the
necessary elements required to focus on conducting research in NFC
technology.
27
The vast amount of literature gives valuable insight into answering the
following research questions:
1. Which variables affect millennials’ attitudes when accepting new
innovative technologies?
2. Do millennial user’s attitudes towards NFC affect their behavioural
intention to adopt the technology?
28
Chapter 3: Methodology
3.1) Introduction
The primary purpose of the research is to gain a deeper understanding of
human behaviour when accepting new technologies, specifically the
behaviour of millennial social media users and NFC technology. This chapter
explains the methodologies that were used for the study. Two schools of
thought concerning research methods are discussed and justification is given
for the chosen case. Following this, the research design and data collection
methods will be discussed, introducing the use of both primary and secondary
data. The questionnaire design will be examined, as well as the manner in
which the data was analysed. Lastly, the validity and ethical considerations of
the methodology will be discussed.
3.2) Research Methodology
In conducting research in social sciences, two main schools of thought need
to be considered when applying methodology - Subjectivism (or
interpretivism) and Positivism. Labelling the difference between these two
schools of thought as the “paradigm war”, Kirby (2007) believes the division of
these two approaches is a simplification of research.
29
According to Kantona and Morgan (1952), positivism refers to a scientific,
objective approach when observing behaviours of human beings that exist in
the natural world. Larrson (1993) further expands on the theory, which begins
with researchers forming hypotheses before gathering and analysing
statistical data to prove or disapprove predetermined theories. Through the
use of statistical analysis, this approach is also commonly referred to as
deductive research according to Kirby (2007). Deductive research can often
misrepresent a researcher’s influence over his or her research by assuming
that the researcher has no control over results. In this study, I found this to be
partially false. While conducting the literature review and forming
predetermined hypotheses, I have included my beliefs and experiences as a
millennial technology and social media user. Therefore, my perspectives have
partially influenced the direction of the study.
When contrasting positivism to subjectivism, Aliaga and Gunderson (2000)
report a Subjectivist approach as a research method where the researcher is
involved with and has influence over or is affected by the study. Synonymous
to subjectivism is the use of subjective research tools such as, but not
restricted to: interviews, focus groups and ethnography, where the researcher
is included directly in the process, which affect outcomes.
The subjective approach yields hypotheses only after data has been
collected, leaving interpretations to be made and patterns to be discovered by
the researcher (Gummesson 2005, Lemke, 1998).
30
Figure 7: (Deduction & Induction, no date)
For the purpose of this paper, a quantitative approach will be utilised to
confirm or disprove hypotheses and theories established earlier in the
literature review. NFC is an innovative technology with a moderate amount of
recent academic interest, which has primarily taken a quantitative approach.
This study has borrowed from a vast amount of literature already conducted
on technology adoption and has adapted it for NFC and millennials in a social
media environment.
For this reason, this study has used a quantitative methodology approach to
expand and interact with previously conducted research.
31
3.3) Research Design
The primary objective of the research was to uncover variables affecting
attitude and adoption of NFC technology among millennials in a social media
environment. Before designing the questionnaire, which was used as a
primary data collection tool, a conceptual model was developed in line with
previous research conducted in the subject area. As explained in the chapter
above, when carrying out a detailed analysis of the variables which affect
millennials’ attitudes towards the acceptance of new technologies, two models
were used to facilitate the design. The models used were the UTAUT by
Venkatesh et al., (2003) and the TAM by Davis (1989). Detailed analysis
revealed the variables Social Influence, Perceived Usefulness and Ease of
use, Compatibility and Perceived Risk influenced the attitudes millennials
formed when accepting new technologies. Drawing from the TAM model, the
attitude was then measured with the intention of using the technology. This
formed the foundation of the conceptual model designed for this study.
Carrying out the study in this way, allowed the research to contribute to the
field of technology acceptance, while touching on millennials’ social
behaviours in the contemporary world powered by social media.
On completing the conceptual model, the questionnaire was designed in line
with the model and proved to be an effective way in the collection of data for
this study.
32
3.4) Data Collection
3.4.1) Secondary Data
Defined as previously accumulated data from earlier forms of research,
secondary data is a vital part of the research process for a quantitative
approach (Saunders, 2007). Saving time and providing a higher quality of
data, secondary data provides the basis for theories and frameworks used in
this paper. Secondary data drawn from the research discussed in the
literature review chapter was used in conjunction with primary data collected
(see section 3.3.2). The data was used to develop the aims and objectives of
the research, as well as formulate theories and hypotheses. The data used in
this paper was accumulated through predominately online sources, including
peer-reviewed journals, books and websites.
3.4.2) Primary Data
In contrast to secondary research, where data is accumulated through
reviewing and borrowing from previous researchers, primary research data is
collected as a direct result of their own implementation of tools or for the case
of this paper, a questionnaire (Saunders, 2007). An online questionnaire
gathers as many responses as possible, with a far greater reach than what
would have otherwise been possible in an offline questionnaire according to
Wiersma (n.d) of the Oxford Internet Institute. I used a convenience sampling
approach via two social media platforms.
33
The sampling approach was chosen because of the convenience of reaching
as many people as possible in a short period of time (Davies, 2007). The
research conducted of millennial social media users, was distributed across
two of the most active social media channels in the contemporary world:
Facebook and Twitter, (Milanovic, 2015). Posted on April 4th, 2016, the
questionnaire had a potential reach of over 3000 potential participants,
especially when sharing and re-tweeting were taken into consideration.
3.5) Questionnaire Design
The online questionnaire was separated into eight sections, making the
progression and understanding for the participant as simple as possible to
hold interest throughout. Fallowfield (1995) notes that respondents find it
easier to answer questionnaires when they are separated into sub-sections,
allowing for consistent participation.
The questionnaire began with a short introduction of NFC technology,
accompanied by a description of how the technology could be used for the
purpose of the study. This was done to explain and educate the participant on
the subject matter to minimise the chance of answering the questions without
any knowledge. (See Appendix 1 for Questionnaire)
34
The first section dealt with demographics (Age and Gender) followed by a
question on experience with the technology, as well as the type of
smartphone the respondent owned. All four questions were multiple-choice
answers.
The remaining seven sections were designed as close-ended questions
(except one in the risk section which will be explained further on). According
to Maylor and Blackmon (2005), more accurate data may be drawn from
close-ended questions compared to open-ended ones, which requires further
interpretation.
The authors continue to highlight the ease with which close-ended question
can be quantified and analysed by the researcher. The close-ended questions
in all seven sections (with an exception of one) were designed using a Five
Point Likert Scale with 1=Strongly Disagree and 5=Strongly Agree. The
writers Maylor and Blackmon (2005) propose Likert scales as being easier for
the respondent to interpret when answering questions and the authors point
out the wide use and popularity of Likert scales throughout academic
research. The limitations of a Likert scale will be discussed further in section
(3.7).
35
3.6) Data Analysis
Considering the nature of the structure of the questionnaire being 95%
closed-ended questions, the data gathered was analysed by using ‘Statistical
Package for the Social Sciences’ (SPSS). This software allowed for in-depth
statistical analysis of the various outcomes. Using descriptive statistics
allowed for processes of understanding through ‘means’ between data sets,
correlations as well as regression analysis and Cronbach’s Alpha to conduct
reliability testing of the data.
Upon dealing with the single open-ended question, answers were analysed in
detail, resulting in finding recurring trends throughout respondents’ answers.
Considering there was only one question of this nature, coding various
themes that occurred throughout the answers to formulate categories or
‘buckets’ was conducted (Zapin, no date). This strategy coupled with
secondary data in the literature review was used to quantify answers for
statistical analysis.
36
3.7) Validity
Drawing from the positivist, quantitative nature of the research, respondents
were able to answer the questionnaire without pressure from any outside
forces (i.e. the researcher) at their pace, and at any location of their choice.
Andrews et al. (2007) further justify the validity of a quantitative methodology
by stating a scientific approach is more suitable for analysing technology
adoption and acceptance. During the process of collecting data for the
research, as mentioned above, a Likert scale was used as the primary
function for respondents to answer questions (except one question). Maylor
and Blackmon (2005) are of the opinion that a Likert scale offers more validity
compared to other forms of answering methods (i.e. multiple choice). The
authors justify their view by explaining the thought process required for
responding to a Likert scale question compared to a multiple choice question,
where answers could be picked at random. Contesting this school of thought,
Podsakoff et al. (2003) highlight a possible problem with Likert scaling. The
authors believe that respondents, afraid of answering with either extreme of
the scale (i.e. 1 or 5), choose answers within the three neutral groups, diluting
the actual attitude of respondents. To keep the questionnaire valid,
respondents were asked only to answer if they were between the ages of 18-
30 years of age. Respondents were assured that all data collected would
remain anonymous and the data would be used only for the purposes of
research only. Hidden identity allowed participants to feel more comfortable
about answering questions truthfully, increasing the validity of the sample.
37
Lastly, according to a study on NFC technology, Chen & Chang (p 616, 2013)
advised that researchers should conduct a pilot review of the questionnaire to
strengthen its reliability and validity. The pilot review was conducted by a
teaching fellow at Royal Holloway University of London as well as a millennial
working in a tech start-up (RoundMenu.com) who had previous knowledge of
NFC technology. Both participants in the pilot study had knowledge and
experience in academic research and were of opposite genders and different
in age which added to their ability to give valuable feedback in order to
streamline the questionnaire.
3.8) Ethical Considerations
The research conducted received approval of ethical procedures from the
Royal Holloway University of London ethics code. (See Appendix 4 for Ethics
Code Certificate)
All data was securely stored on Google Docs with only the researcher and
supervisor having access to any information from the questionnaire
participants.
38
Chapter 4: Findings
This chapter will present the raw findings collected from the primary data
questionnaire discussed in the chapter above. This is separated into four
sections dealing with frequency statistics, reliability testing, descriptive
statistics, hypothesis testing and regression analysis.
4.1) Demographics
The questionnaire began with the demographics of respondents. Analysing
the frequency of the 103 millennial responses below gives the reader a clear
idea about who participated in the questionnaire, as well as their experience
with the technology before participating in the study.
4.1.1) Age
As displayed in the pie chart below, 69% of respondents fell into the 22-25-
year-old category followed by 27% in the 26-30-year-old category, with only
4% of respondents falling into the youngest 18-21-year-old grouping.
39
Figure 8: Age Demographics (Source: own contribution)
4.1.2) Gender
The pie chart below shows dominance of male respondents, with 68% and
32% female.
Figure 9: Gender (Source: own contribution)
40
4.1.3) Smartphone ownership
The majority of respondents, 62.2%, owned an Apple iPhone. Half as many
respondents were Samsung owners with 32.1% and only 1.9% of
respondents owned a Blackberry. Lastly, 5.9% of respondents stated owning
a smartphone other than the three mentioned.
Figure 10: Smartphone type (Source: own contribution)
41
4.1.4) Experience with NFC technology
As displayed in the pie chart below, a significant percentage of respondents
had never used NFC technology services (59%). 12% of respondents were
not sure if they had encountered the technology, and 29% stated they had
previously used NFC.
Figure 11: Experience with NFC (Source: own contribution)
42
4.2) Reliability Testing
Drawing from the research of Dutot, (2015);; Chen & Chang, (2013);;
Pham & Ho, (2015), using a Cronbach's Coefficient Alpha as a measurement
of reliability is the most common statistical reliability test for Likert scale
answers. Bryman and Bell (2007) state that an alpha below .70 is deemed
unreliable. The authors continue by explaining this only to be true for scales
with ten or more items. Due to this study containing a maximum of three items
per construct, alphas below .70 commonly arise according to Bryman and Bell
(2007). An alpha of one (1) indicates a perfect internal reliability and 0
showing no internal reliability. As displayed in the table below, all constructs
rendered medium to high internal reliability alphas.
Table 1: Reliability Test (Source: own contribution)
43
4.3) Descriptive Statistics
Having met minimum requirements for validity of the questionnaire, the focus
will be shifted onto the descriptive statistics of each construct, by looking
specifically at the mean, mode and standard deviation of each question.
Davies (2007, pp. 124-125) clearly highlights the importance of using
measures of central tendency as the bedrock for further exploration into the
findings of a given data set. The mean and mode values were used in order
“to provide information about the centre of a distribution of values” (Larson, p.
77, 2006). The mean is an average of the total responses to each question
and the mode is the most frequent recurring response in a particular answer
(Larson, 2006). Using the information provided by respondents of the primary
data, the mean and the mode offer insight as to how respondents perceived
NFC technology in a social media setting. As shown in the result tables below,
each construct is grouped with each question being numbered per the order in
which it appeared in the questionnaire (i.e. Perceived Usefulness = PU_1,
PU_2, etc.). Considering the answering method was constructed in a Likert
scale format with 1= Strongly Disagree and 5= Strongly Agree, an average
mean of 3 and above was accepted as being a positive indication. The same
was true for the mode values, 3 and higher. The rationale for accepting an
average mean of 3 and average mode of 3 is drawn from an earlier stated
limitation concerning Likert scales, where Podsakoff et al. (2003) stated that
respondents were often uncomfortable answering a scale question with either
extreme (in this case 1 or 5).
44
According to Larson (2006), dispersion statistics, variance and standard
deviation offer researchers valuable statistical information concerning the
“variability of the data about the measures of central tendency” (p. 77). The
standard deviation is the distance that a variable deviated from the mean, with
a lower standard deviation showing a more consistent set of results.
45
4.3.1) Perceived Usefulness
The construct of Perceived Usefulness (PU) was adapted from the
Technology Acceptance Model (TAM) created by Davis (1989). Having been
further adapted for NFC technology, it was used to gauge the Perceived
Usefulness of NFC for social media among millennials. The results showed
millennials’ perceiving the use of the technology for social media as useful
with a mean of 3.36 and a mode showing high responsiveness with an
average of 3.33 throughout the three questions.
Table 2: Descriptive Statistics Perceived Usefulness (Source: own contribution)
46
4.3.2) Perceived Ease of Use
The construct of Perceived Ease of Use (PEU) from Davis (1989), further
adapted for NFC technology, was used to understand the manner in which
millennials perceive how easy it is to use NFC technology. With a mean value
of 4.40 and a mode of 5, clear evidence is given as to the extent millennials
perceive NFC technology to be easy to use.
Table 3: Descriptive Statistics Perceived Ease of Use (Source: own contribution)
47
4.3.3) Social Influence
The construct of Social Influence (SI) from the Unified Theory of Acceptance
and Use of Technology (UTAUT) model by Venkatesh et al. (2003), further
adapted for NFC technology, was used in order to uncover whether
millennials are influenced by their social surroundings (i.e. friends, family, role
models) when accepting new technology. Keeping in line with the opinion of
Fromm et al. (2011) quoted in the literature review;; millennials are influenced
by their social surroundings when accepting new technology. This was
evident to see with a mean of 3.085 and a mode of 3.5,
Table 4: Descriptive Statistics- Social Influence (Source: own contribution)
48
4.3.4) Compatibility
The construct of Compatibility (Com) from Yang et al., (2012), further adapted
for NFC technology, was used to understand to what extent respondents
valued the compatibility of the technology to their social media activities.
According to Pham and Ho (2015), the extent to which a user finds a
technology compatible with their lifestyle (in this case social media) the more
willing the user will be to accept the technology. With a mean and mode of
3.5, clear evidence is given that users perceive NFC technology to be
compatible with their social media activities.
Table 5: Descriptive Statistics- Compatibility (Source: own contribution)
49
4.3.5) Perceived Risk
The construct of Perceived Risk from Brown et al., (2003) and Pham and Ho
(2015) was to understand the perceived risk respondents felt towards NFC
technology for social media activities. As shown in the table below, a mean of
3.11 and mode of 3.5 proves that respondents felt NFC technology would
have a high level of risk when used in a social media capacity. Interestingly,
Risk_1 rendered a low mean value, and this finding will be discussed later in
the chapter.
Table 6: Descriptive Statistics- Risk (Source: own contribution)
50
4.3.6) Attitude towards Use
The construct of Attitude towards use (Att) from Davis’ (1989) TAM and
Venkatesh et al.’s (2003) UTAUT model, further adapted for NFC, is used to
uncover the attitudes respondents have towards accepting the use of NFC
technology for social media activities. With an average mean of 3.46 and
average mode of 3.5;; respondents’ attitudes were positive when considering
the use of NFC technology in a social media capacity.
Table 7: Descriptive Statistics- Attitude Towards Use (Source: own contribution)
51
4.3.7) Behavioural Intention
The construct of Behavioural Intention to accept technology was adapted from
Davis’ (1989) TAM and Venkatesh et al.’s (2003) UTAUT model. The
construct was used to understand respondents’ behavioural intention to
accept NFC technology in a social media capacity. With an average mean of
2.81 and mode of 3, it can be noted that a neutral to negative response
towards behavioural intention was discovered. Although a mode of 3 showed
positive signs, a mean of less than 3 indicates users’ lack of intention to
accept the technology. These statistics could be influenced by many factors,
including a lack of knowledge of the technology to make an informed decision
about a user's intention to use NFC.
Table 8: Descriptive Statistics- Behaviour Intention (Source: own contribution)
52
4.4) Hypothesis Testing and Regression Analysis
4.4.1) Hypothesis Testing
To conduct reliable hypothesis testing, Pearson’s correlation coefficient
measures the strength of a linear association between two variables, and has
been implemented due to the data being normally distributed (Field, 2009).
The correlation coefficient is always between (-1 and 1). Positive one (1)
indicates perfect positive and negative one (-1) indicates perfect negative
(Field, 2009). (See Appendix 2 for raw SPSS statistics)
SI: Social Influence, PU: Perceived Usefulness, PEU: Perceived Ease of Use, Com: Compatibility, Risk, Att: Attitude Towards Use, BI: Behavioural Intention
Table 9: Hypothesis Testing (Source: own contribution)
53
H1: Social Influence à Attitude
• There is a positive relationship between Attitude towards the use of NFC
and the Social Influence experienced by a millennial user.
.574 from Table 9 indicates there to be a moderately strong positive
correlation between Social Influence and Attitude towards NFC technology.
The significance level is 0.01
.000 < .01 = There is enough evidence to suggest that the correlation
observed does exist in the population and therefore Hypothesis 1 stands.
H2: Perceived Usefulness à Attitude
• There is a positive relationship between Attitude towards the use of NFC
and the perceived usefulness of the technology by a millennial user.
.691 from Table 9 indicates there to be strong positive correlation between
Perceived Usefulness and Attitude towards NFC technology.
The significance level is 0.01
.000 < .01 = There is enough evidence to suggest that the correlation
observed does exist in the population and therefore Hypothesis 2 stands.
54
H3: Perceived Ease of Use à Attitude
• There is a positive relationship between Attitude towards the use of NFC
and the Perceived Ease of Use of the technology by a millennial user.
.280 from Table 9 indicates there to be weak positive correlation between
Perceived Ease of Use and Attitude towards NFC technology.
The significance level is 0.01
.004 < .001 = There is enough evidence to suggest that the correlation
observed does exist in the population and therefore Hypothesis 3 stands.
H4: Compatibility à Attitude
• There is a positive relationship between Attitude towards the use of NFC
and the compatibility in a millennial user's lifestyle.
.709 from Table 9 indicates there to be strong positive correlation between
Perceived Ease of Use and Attitude towards NFC technology.
The significance level is 0.01
.000 < .001 = There is enough evidence to suggest that the correlation
observed does exist in the population and therefore Hypothesis 4 stands.
55
H5: Risk à Attitude
• There is a negative relationship between Attitude towards the use of NFC
and the Perceived Risk associated with the technology experienced by a
millennial user.
-.085 from table 9 indicates there to be weak negative correlation between
Perceived Risk and Attitude towards NFC technology.
The significance level is 0.01
.393 > .001 = There is not enough evidence to suggest the correlation and
therefore Hypothesis 4 is rejected.
Qualitative: Open-ended question.
In support of the above findings, the qualitative data collected identified key
concerns of risk when using NFC technology for social media. Of the 103
millennial respondents to the questionnaire, only 39 agreed to elaborate
further on what they perceive as the risks of using NFC. I identified three main
themes in the set of answers:
1. Privacy Concerns (Social Media Information): 30% (12 respondents)
expressed privacy of social media profile information as a risk
associated with NFC.
56
2. Privacy concerns (Personal Information): 40% (15 respondents)
raised concerns about vulnerability to hackers of personal information
with regards to identifying theft and credit card fraud as being a
potential risk when using NFC technology for social media purposes.
3. Accidental Use: 30% (12 respondents) expressed accidental and non-
intentional use of NFC as a potential risk associated with the
technology.
H6: Attitude à Intention
• Millennial Social Media user’s attitude towards NFC has a significant
positive relationship with the users Behavioural Intention to use the
technology.
.709 from table 9 indicates there to be a strong positive correlation between
Attitude towards NFC technology and Behavioural Intention to adopt the
technology.
The significance level is 0.01
.000 < .001 = There is enough evidence to suggest that the correlation
observed does exist in the population and therefore Hypothesis 6 stands.
57
4.4.2) Regression Analysis
The next two regression analysis tables will describe the relationship between
Social Influence (SI), Perceived Usefulness (PU), Perceived Ease of Use
(PEU), Compatibility (Com), Perceived Risk (Risk) and Attitude Towards Use
(Att). The tables will indicate if the conceptual model was successful in
predicting the outcomes of millennials’ attitudes toward the use of NFC. As
noted in Table 10 below, Attitude Towards Use has been used as the
dependent variable and Perceived Risk, Perceived Ease of Use, Perceived
Usefulness, Social Influence and Compatibility as the predictors influencing it
(Field, 2009).
• R in column one indicates a strong positive correlation between the five
predictors and the attitude millennials formed towards the use of NFC.
• R-squared in column two of the table 10, is the measure of how much
of the variability in attitude of use is accounted for by the predictors.
The five predictors account for 61.4% of the variation in attitude
towards the use of the NFC.
• Column three in Table 10 provides evidence of how well the conceptual
model has generalised for the population of respondents. With a
difference between Adjusted R-squared and R-squared being (.614-
.594= 0.02) = 2%, this indicates that if the entire population were to be
used in place of the sample selected, there would only be a shrinkage
of 2%, showing a positive cross-validity of the model.
58
Model Summary
Predictors (Constant): SI, PU, PEU, COM, RISK Dependent Variable: Attitude towards use
Table 10: Regression Analysis (Source: own contribution)
As shown in Table 11 below, a significance level of p < .001 (.000<0.001)
indicates that the framework significantly improved the ability to predict
millennials’ attitudes toward the use of NFC (Field, 2009).
59
ANOVA
Table 11: Significance Testing (Source: own contribution)
60
Chapter 5: Discussion of Findings
Chen and Chang (2013, p.621), state that NFC technology is a “combination
between innovative technology and an information system”. This justifies the
use of the TAM and UTAUT models to explore behavioural intention through
the moderating construct of attitude toward use of NFC. Using the conceptual
model, I highlighted six hypotheses, which were then tested through the
online questionnaire. The significance of these findings will be discussed
below.
5.1) Social Influence and Perceived Ease of Use
The construct of Social Influence (SI) was in line with the literature reviewed.
The research found that millennials' attitudes towards NFC technology was
positively influenced by their social surroundings (i.e. friends, family and role
models).
Perceived Ease of Use (PEU) scored poorly in the research, which was not
initially hypothesised. Although still rendering a positive relationship with
attitude, the results showed that when millennials form attitudes towards NFC,
Perceived Ease of Use was not considered as being an important factor.
Hence, the weak positive correlation between the two constructs.
61
5.2) Compatibility and Perceived Usefulness
The research showed Perceived Usefulness and Compatibility as the two
most important constructs influencing millennials’ attitudes towards the use of
NFC. These results were in line with previous studies of NFC technology,
where compatibility to a user’s lifestyle and perceived practicality of the
technology were deemed as the most influential factors in the adoption
process, (Pham & Ho, (2015), Everett M. Rogers, (1995), Agarwal & Prasad,
(n.d.)). The study conducted by Pham & Ho (2015), resulted in Perceived
Usefulness surpassing Compatibility as the most influential factor in the
technology acceptance process. This study however, proved the opposite to
be true. While both were instrumental in the formation of attitudes,
compatibility surpassed perceived usefulness significantly. This suggests that
millennials are more concerned with how NFC technology complemented their
social media environment, more so than any other construct.
5.3) Perceived Risk
Contradicting all previous literature reviewed, Perceived Risk showed no
significance in its influence over millennials’ attitudes when accepting NFC
technology. Dutot (2015), Pham and Ho (2015) and Chen and Chang (2013),
being the most recent studies of NFC technology adoption, all concluded that
risk has a significant influence on the formation of attitude and the behavioural
intention to adopt NFC.
62
Taking into account all of these studies focused on NFC payment related
subjects, where perceived risk was associated with fraud, theft and possible
interception of transactions, this study initially hypothesised there to be a
similar relationship between Risk and Attitude with social media contact
sharing. The rejection of this assumption came as a surprise. The millennial
respondents provided evidence that risk did not influence their attitudes
towards using the technology. Due to the surprising nature of this finding, a
more detailed analysis was conducted.
Question 1 of the “Perceived Risk” construct in the questionnaire asked:
“Using NFC for social media has risks and makes me feel insecure.”
The mean answer to this question was 2.84 as displayed in Table 6. This
indicates that respondents were positioned below the acceptable mean
response of 3. This suggests millennials do not perceive risk as a significant
influence when forming attitudes towards the adoption of NFC for social
media contact sharing.
Question 2 of the “Perceived Risk” construct in the questionnaire asked:
“Using NFC for social media could make my personal information (other
than social media information) known to others I do not intend to share
with”.
Showing more normal results (concerning previous research), the mean
answer to this question was slightly higher equalling 3.38 and a mode answer
of 4.
63
This deeper analysis suggests millennials are more concerned with personal
information (i.e. phone number, address details, identity information and credit
card details) rather than social media information, falling into the wrong
hands. This is in line with the secondary research.
While the latter seemed significant, millennials did not feel insecure when it
came to risks of the technology in a social media capacity.
5.4) Attitude Toward Use and Behavioural Intention to Adopt
Taking from the regression analysis in Table 10, it is evident that the
constructs of Social Influence, Perceived Usefulness, Perceived Ease of Use,
Compatibility and Perceived Risk account for 62% of the variability in the
dependent variable of Attitude Towards Use of NFC. Field (2009) confirms
this value to be very high when conducting regression analysis.
Attitude toward use was then measured against behavioural intention to adopt
NFC in a social media capacity. The original hypothesis stated there to be a
significant positive relationship between these two constructs. The results
proved this to be correct. With a strong relationship, it can be concluded that
the formation of a positive attitude toward NFC will lead to a high intention to
adopt the technology among millennials.
64
Considering the above-discussed findings, this research questionnaire and
conceptual model may be considered a success as it proves there to be a
direct positive relationship between attitudes formed and intention to adopt
NFC technology for social media contact sharing.
65
Chapter 6: Conclusion
6.1) Contribution
This research offers future practitioners and academics a robust framework
for analysing NFC technology adoption. The framework can be implemented
for other innovative technologies and not solely for NFC.
6.1.1 Academic Contribution
Considering NFC is a new technological phenomenon, this research offered
one of the first of its kind, linking NFC technology and social media contact
sharing, looking specifically at millennials. The secondary literature reviewed
had relatively few areas of focus for NFC technology, specifically in the peer-
to-peer functionality, resulting in this paper developing a new area of
knowledge. This research provided a framework structured to understand the
millennial consumer by identifying the key factors influencing attitude
formation. The study provided sufficient evidence that millennials’ attitudes
positively affected their intention to adopt NFC for social media contact
sharing.
66
6.1.2 Applied Contribution
The study underlines the key factors influencing the formation of attitude
towards the use of NFC as Perceived Usefulness but more importantly,
Compatibly. Furthermore, the research displayed there to be a significant
positive relationship between millennials’ attitudes and their behavioural
intention to adopt the technology for social media. Considering respondents in
this research were concerned with the risk of personal information being
shared, potential service providers looking to promote NFC services in social
media would benefit from assuring consumers that NFC does not hold risk
implications of hacking or interception of personal information (i.e. credit
cards, identification, etc.). Furthermore, marketers’ looking to attract millennial
consumers, should allocate resources towards highlighting the compatibility
the product provides as well as the usefulness of the product in a social media
environment.
6.2) Limitations and Future Research Direction
This study encountered limitations throughout its duration. Firstly, the
constraint of time affected deeper research and understanding of the topic.
With additional time, more data could have been collected, resulting in a
richer analysis.
67
Secondly, the limitations of the size of the study restricted deeper explanation
and examination of the literature, as well as the primary data collected.
Initially, the pilot study was perceived as being sufficient for the release of the
questionnaire. Yet, in retrospect a more thorough pilot study should have
been conducted.
Future research into the subject area should consider using a larger sample
size, with a wider demographic spread. Also, more qualitative research could
be utilised in conjunction with the quantitative approach to gain a deeper,
more personal understanding of each respondent. Lastly, due to the discovery
of perceived risk contradicting prior research, the questions concerning risk in
the questionnaire could be re-analysed. The pilot study did not show its flaws
initially but throughout the investigation it appeared that a perceived risk
question could have confused the respondents, which possibly explains the
contradictory risk findings. Future research could prove or disprove this
theory.
Continuing this research, I plan to implement this framework into other areas
of innovative technology to test the applicability of the conceptual model.
68
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Appendix
1) Questionnaire
80
81
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83
84
85
86
2) Hypothesis Testing Social Influence
87
Perceived Usefulness
88
Perceived Ease Of Use
89
Compatibility
90
Perceived Risk
91
Behavioural Intention
92
3) Regression Analysis – Model Summary
Regression Analysis -‐‑ Anova
93
3) Ethics Code
94