Bachelor Thesis
Augmented Reality
- The current and potential use of augmented reality in B2B
Authors: Azjargal Gankhuyag Bingqing Xiang Victoria Bonnevie Supervisor: Peter Caesar Examiner: Pejvak Oghazi Date: 2015-05-29
Subject: International Sales and
Augmented Reality
- The current and potential use of augmented reality in B2B
Azjargal Gankhuyag Bingqing Xiang
&
Victoria Bonnevie
Linnaeus University
Ekonomihögskolan, Department of Marketing International Sales and Marketing
Spring 2015
Abstract
In today’s world, we live in a technologically advanced environment where information access is huge and limitless. The advantage to this is that, people are able to create more information, share and communicate with each other instantly on the go regardless of where they are in the world. However on the downside, with endless information, it becomes confusing and difficult to filter which information is right for a person’s need.
This goes hand-in-hand for business companies, as it requires strategic processes and tools to identify the information from the market, store and evaluate it into meaningful insights and lastly communicate it efficiently so that the value of it is not lost along the way. Therefore this study focuses on how augmented reality (AR) as an emerging digital technology is able to dissect and communicate information and bring value to those who are implementing it. What is more interesting in this study is to see the usefulness and ease of using AR from commercial and non-commercial aspects in B2B field. This study was conducted through a qualitative research approach with semi- structured interviews with five companies providing and using AR applications. In conclusion, AR brings value by transferring data faster and communicating it effectively through visualization of integrating computer-generated information with the real world as one. From commercial aspect, companies could use this technology in their
marketing communication to increase customer involvement and perception of the brand. In contrast, from non-commercial perspective, companies could use AR as an internal resource to increase efficiency in operation process.
Key words
Augmented reality (AR), Visualization, 3D, Smart devices, Smart glasses, B2B, Technology acceptance model (TAM), Perceived usefulness, Perceived ease of use, Marketing, Competitive-advantage, Market vision
Acknowledgments
This thesis would not be where it is today if it was not for all the people that supported us with tremendous encouragement and inspiration. With their guidance and input this experience has been very rewarding and we are more curious and hungry for
knowledge than ever before.
First and foremost, we would like to thank our examiner Dr. Pejvak Oghazi and supervisor Peter Caesar for guiding us with great help from the very start to the finish line. In many ways their knowledge and feeback help shape our research process and tackle all the obstacles along the way.
We would also like to express our gratitude to all the companies that participated and took part in this study. Without their knowledge contribution and participation we would not have been able to transform our academic interest into a tangible result.
Hence we are grateful for Christer Lundevall, Guillaume Favreau, Kim Bleshøy Nielsen, Matthew Trubow, Niklas Rengfors and Staffan Hagberg.
Lastly, we would like to thank our families who have been there for us throughout our academic years and for always supporting us. Thank you for pushing us like there are no limits and making us believe in ourselves and strive for the best.
Ljungby, May 2015
Azjargal Gankhuyag, Bingqing Xiang and Victoria Bonnevie
Table of contents
1 Introduction _________________________________________________________ 1 1.1 Background ______________________________________________________ 2 1.2 Problem discussion ________________________________________________ 3 1.3 Purpose _________________________________________________________ 4 1.4 Research Questions _______________________________________________ 4 1.5 Delimitations ____________________________________________________ 4 2 Theoretical Framework _______________________________________________ 6 2.1 Business-to-business _______________________________________________ 6 2.2 Marketing Strategy ________________________________________________ 6 2.3 Integrated Marketing Communication _________________________________ 7 2.4 Customer-perceived value __________________________________________ 7 2.5 Market Vision ____________________________________________________ 8 2.6 Technology and knowledge transfer___________________________________ 8 2.7 Experiential marketing _____________________________________________ 9 2.8 Resource-based view model ________________________________________ 10 2.9 Augmented Reality _______________________________________________ 10 2.9.1 Definition of augmented reality __________________________________ 10 2.9.2 Applications of augmented reality ________________________________ 11 2.10 Technology acceptance model _____________________________________ 11 2.10.1 Unified theory of acceptance and use of technology _________________ 12 3 Methodology ________________________________________________________ 13 3.1 Research approach _______________________________________________ 13 3.1.1 Inductive vs. deductive research approaches _______________________ 13 3.1.2 Quantitative and qualitative research _____________________________ 14 3.2 Research design _________________________________________________ 15 3.2.1 Research strategy ____________________________________________ 16 3.2.2 Research sources _____________________________________________ 17 3.3 Data method ____________________________________________________ 18 3.3.1 Data collection method and instruments ___________________________ 18 3.3.2 Operationalization ____________________________________________ 19 3.3.3 Interview guide ______________________________________________ 21 3.3.4 Sample selection _____________________________________________ 22 3.3.5 Data analysis method _________________________________________ 24 3.4 Quality Criteria __________________________________________________ 25 3.4.1 Content validity ______________________________________________ 26 3.4.2 Construct validity ____________________________________________ 26 3.4.3 External validity _____________________________________________ 26 3.4.4 Reliability __________________________________________________ 27 4 Empirical data ______________________________________________________ 28 4.1 XMReality _____________________________________________________ 28
4.1.1 Background and AR ___________________________________________ 28 4.1.2 Marketing Strategy ___________________________________________ 28 4.1.3 TAM _______________________________________________________ 29 4.1.4 Challenges and future outlook ___________________________________ 29 4.2 Intertisement ____________________________________________________ 30 4.2.1 Background and AR ___________________________________________ 30 4.2.2 Marketing Strategy ___________________________________________ 30 4.2.3 TAM _______________________________________________________ 32 4.2.4 Challenges and future outlook ___________________________________ 33 4.3 Animech Technologies ____________________________________________ 34 4.3.1 Background and AR ___________________________________________ 34 4.3.2 Marketing Strategy ___________________________________________ 35 4.3.3 TAM _______________________________________________________ 36 4.3.4 Challenges and future outlook ___________________________________ 37 4.4 Hidden Creative _________________________________________________ 37 4.4.1 Background and AR ___________________________________________ 37 4.4.2 Marketing Strategy ___________________________________________ 38 4.4.3 TAM _______________________________________________________ 39 4.4.4 Challenges and future outlook ___________________________________ 40 4.5 Volvo Group ____________________________________________________ 40 4.5.1 Background and AR ___________________________________________ 40 4.5.2 Marketing strategy ____________________________________________ 41 4.5.3 TAM _______________________________________________________ 42 4.5.4 Challenges and future outlook ___________________________________ 44 5 Analysis ____________________________________________________________ 46 5.1 Augmented Reality _______________________________________________ 46 5.2 Marketing Strategy _______________________________________________ 48 5.2.1 Competitive advantage ________________________________________ 49 5.2.2 Market vision ________________________________________________ 50 5.3 TAM __________________________________________________________ 51 5.3.1 Perceived usefulness __________________________________________ 51 5.3.2 Perceived ease of use __________________________________________ 52 5.3.3 Social influence ______________________________________________ 53 5.4 Challenges and future outlook ______________________________________ 54 6 Conclusion _________________________________________________________ 55 6.1 Theoretical Implications ___________________________________________ 57 6.2 Managerial Implications ___________________________________________ 58 6.3 Limitations _____________________________________________________ 60 6.4 Further research _________________________________________________ 61 7 References__________________________________________________________ 62
8 Appendices _________________________________________________________ 67 8.1 Appedix A: Interview Questions ____________________________________ 67 8.2 Appendix B – Interview Transcripts _________________________________ 68 8.3 Appendix C – List of companies contacted ___________________________ 104
List of Figures
Figure 1. Conceptual framework of inward technology transfer... 8
Figure 2. Data analysis in qualitative research...25
Figure 3. Checklist: Implementation of AR………59
Figure 4. Checklist: Challenges of implementing AR……….60
List of tables
Table 1. Some common contrasts between quantitative and qualitative research ... 14Table 2. A comparison of basic research designs...15
Table 3. Relevant situations for different research methods...17
Table 4. Qualitative data collection types, options, advantages and limitations...19
Table 5. The Operationalization of theories and concepts...20
Table 6. Companies participated in the study...24
Table 7. The participant companies’ perception of AR... 46
Table 8. The companies’ AR offers and use with tools... 48
1 Introduction
There is an explosion of big data, as the digital landscape grows new technologies is able to generate more data than ever before and it is changing the nature of information management and how it is communicated (Boyd and Crawford, 2012; McAfee and Brynjolfsson, 2011). As a result there are two main concerns that challenge business organizations today, firstly, they have more data than they can use effectively due to its steady increase in volume and variety (IMB, 2011). Lastly, the traditional and standard tools such as reporting and spreadsheets are no longer efficient nor capable to support and communicate the useful information filtered from the data to the right recipients (Lavalle et al, 2011). Especially, if business executives want to obtain full value and deliver it both internally within the organization and externally to the customers, they would have to focus on not just providing the right information but make it “come alive” (Lavalle et al, 2011). Hence there are emerging approaches or digital applications that make the information intelligent through visualization and interaction as well as process simulation and other techniques (McAfee and Brynjolfsson, 2011). These approaches also transform the insight information into a simple and easily
understandable resource that can be acted upon at every skill level and function in an organization (Lavalle et al, 2011).
One of these emerging approaches and trending in the market place is Augmented Reality (AR). The concept of AR refers to information in real-time being enhanced and made intelligent with the help of smart devices and applications such as smart phones, tablets, wearable headsets and immersive technologies (Wu et al, 2013). Moreover it supplements the real world environments with virtual, computer-generated digital information, allowing a user to experience the interaction between the two worlds (Azuma, 1997; Azuma et al, 2001). Therefore the ways in which information is made available, presented and experienced by users are also changing with augmenting the real world with digital information (Olsson et al, 2012).
AR in the recent years has been integrated in many business areas, such as from marketing and sales perspective, AR provides visualization of products from clients to the customers without the limitation of size and location (Hidden Creative, 2011).
Looking particularly from business-to-business (B2B) perspective, such as at trade shows, it is very hard and almost impossible to bring real-life products as they tend to
be big in size and costly. Hence visitors and customers normally get brochures and product catalogues to browse through to gain perception of the value that they are looking for. However with AR, businesses are able to bring industrial products “come alive” in 3-dimensions (3D) and in real-time, which enhances the marketing
communication (Hidden Creative). Further, the virtual objects or visualization of products can display information that a user cannot directly see on a paper or perceive with the human senses (Azuma, 1997). This human-digital interaction also allows a user to perform real-world tasks, such as in manufacturing sector, a job that requires a hands- on approach with specification and instruction requirements could benefit greatly from AR solutions (Krevelen and Peolman, 2010; ItNow, 2014). Further, with the
combination of ubiquitous computing, smart services becoming available anytime and almost anywhere, AR enables users to naturally interact in the everyday real world while allowing users to efficiently utilize both their own skills and the power of networked computing (Olsson et al, 2012).
1.1 Background
Augmented reality was first tapped by Ivan Sutherland, a computer graphic pioneer, in the late 1960’s (Krevelen and Peolman, 2010). He and his students at Harvard
University used the first see-through head-mounted display (HMD) system to present 3D graphics (Azuma, 2001). However it wasn’t until the early 1990’s that this
technology was given an official term “augmented reality” coined by two scientists at Boeing Corporation named Thomas Caudell and David Mizell (Krevelen and Peolman, 2010). The two scientists built an experimental AR system that is see-through display to guide the workers to assemble long bundles of wires for the new 777 jetliner (MIT Technology Review, 2014). Since then the potentials of AR was recognized by more researchers and by the late 1990’s several conferences on AR began, such as the
International Workshop and Symposium on augmented reality (Krevelen and Poelman, 2010).
In 2004, in Germany, a group of researchers brought see-through technology to cell phones and by 2009 it became possible with ARToolkit to build AR applications with software toolkits on web browsers freely (Tom’s Hardware, 2014). With the
technological advancement in today’s smart devices and applications, the support needed to integrate the many years of experimental research and progress in
registration, tracking and calibration of AR is now finally available (Liao, 2015). This is consequently generating much public interest around AR as it has become both
economically and technically viable for public use (Olsson et al, 2012). Further, the time AR was first publically introduced to the general masses and generated hype was most certainly when Google unveiled the “Project glass” or “Google glass” in 2012 (Echeva and Pedersen, 2014). Google promoted this project with the YouTube video of
“One day” showcasing and promising the masses that their interpersonal connectivity will be enhanced and accessed through computer-generated graphics superimposed in their field of vision (Echeva and Pedersen, 2014). Other companies such as Epson, Vuzix and more, have also developed or developing their own smart glasses. Moreover with Google’s Android and Apple’s iOS operating systems, developing and using AR applications have become viable. Most recently, in March 2014, Facebook acquired Oculus VR, creator of the Oculus Rift virtual reality headset for $2 billion creating headlines all over the world (The Guardian, 2014). Facebook’s founder and CEO Mark Zuckerberg, shares his vision and believes that “immersive and augmented reality will become a part of daily life for billions of people” (Zuckerberg, Facebook, 2014). Hence AR’s growth and progress has been significant and there is more to look forward to.
1.2 Problem discussion
With AR, there is a focus on “interactivity” and “digitalization” elements which combined work in unison to ultimately and creatively communicate useful information between the sender and the user. As there are different applications to AR, it is
interesting to identify how information is being communicated through the use of AR application in B2B and to what result.
Moreover there is a fundamental shift in the market due to the continuous advancement in innovation technology and internet (Järvinen et al, 2012). As a result customers are empowered and using advanced technology in their everyday lives (IBM, 2011).
Customer preferences are also constantly changing which leads to an incessant search for new and better products and services (Gebauer et al, 2011). This requires companies to be market-driven, meaning that they should be able to generate, disseminate and productively use information about customers and competitors to identify the changes (Hutt and Speh, 2010). Finally, deliver value through matching customers’ everyday use of technological devices and applications at home and workplaces (Winer, 2009). Hence
with the combination of the advancement in technology and changing customer preferences with an instant “click” away from information access and sharing, businesses are aware of the pressure and believe in investing in new technologies. As well as innovative activities if they wish to deliver superior performance and attain competitive advantage to differentiate themselves from the competition (IBM, 2011;
Gebauer et al, 2011; Lavalle et al, 2011). Therefore with the potential values of AR and given that it is an emerging technology with a lack of research in the B2B field, it sparks an interest and motivation for this study to assess the current and future application of AR in B2B organizations both from commercial and non-commercial aspects. The aim is to find out if AR is able to transform information and communicate it easily to the designated recipients. As well as to obtain a further understanding on the challenges and limitations companies would face when investing and implementing this interactive technology.
1.3 Purpose
To identify if AR as an emerging tool is able to communicate information effectively (easier to communicate and understand) from commercial and non-commercial aspects in B2B sector.
1.4 Research Questions
RQ1: Does AR make information easier to communicate and understand?
RQ2: Could AR provide competitive advantage to improve marketing?
RQ3: What are the current perceived potentials of AR?
1.5 Delimitations
Initially the authors wanted to conduct the study from two perspectives, one from the provider’s and the other from the customer’s who use AR solutions. The reasoning behind this was to cover all sides of the market use of AR that could be applicable across all B2B, not just from one side. However the study is conducted from the
perspectives of companies that provide AR solution to B2B customers and hence act as a delimitation. Another concern is that, as the study centers the European market, the study range is narrow and will not be applicable in other markets. Furthermore there are very limited secondary data on AR both from commercial and non-commercial aspect in
B2B and this was a disadvantage for the authors to gather background to the topic of AR. Lastly, as it is an emerging technology, there are limited amount of companies found in using AR in their organization, hence the authors could not choose one specific industry to base this study on. To further elaborate, as it is based mostly on the
providers’ point of views, their customers who are using AR in their organizations are located across different industries.
2 Theoretical Framework
In this chapter, firstly, the authors distinguish and emphasize B2B from B2C markets and marketing strategy is dicussed next to give an overall view of how a market operates. Moving on, the concepts of augmented reality is explained further as well as its applications. Lastly the chapter brings a focus on the criteria that influence user’s evaluation of AR as an emerging technology.
2.1 Business-to-business
B2B refers to the markets selling and purshacing goods and services between organizations such as businesses, governments and institutions. Hence the monetary volume of transactions are significantly higher than the consumer market and as there is more at stake and the decision-making process is relatively longer as well. Moreover, there is a focus on fostering long term customer-relationship due to that a single customer can be accountable for a great deal of purchasing activity. Business
organizations “buy industrial goods to form or facilitate the production process or use as components for other goods and services” (Hutt and Speh, 2010, p. 4).
2.2 Marketing Strategy
Marketing strategy is the most important approach to consider when it comes to creating a product value proposition to capture customers’ attentions (Solomon, 2013).
According to Kotler and Armstrong (2012) marketing strategy is “the marketing logic by which the company hopes to create a customer value and achieve profitable customer relationships” (Glossary G5). Hence to be able to achieve competitive advantage within the high-pressure competition, a company has to search different ways to deliver
exceptional customer value in its marketing strategy (Shamma and Hassan, 2013). In addition, marketing strategy can be viewed as a competitive advantage developed by a company to provide a superior customer value, andto differentiate its products by either having lower prices or providing more benefits that justify higher prices (Kotler,
Armstrong, 2012). Therefore, as digital marketing is becoming more and more
integrated and emphazised by companies in the dynamic markering environment, it also
acts as a communication tool with competitive advantage that can strengthen a company’s developed value proposition over other competitors. From the point of differentiation, more manufacturing companies are intending to increase the investment in the service differentiation in their market strategy in order to capture and maintain more customer (Gebauer et al, 2011).
2.3 Integrated Marketing Communication
Due to the rise in large number of new media, the nature of the communications model has been changed to what is now called a “hypermedia” environment (Winer 2009).
Hence there is more focus on specialized integration and highly targeted media in order to reach segmented customers as they are now interacting with the company, with each other and rest of the world through social networking and other new media (Kotler and Armstrong, 2012). This shift to the richer mix of media and communication has lead to the concept of integrated marketing communications (IMC) and it was first stated by the American Association of Advertising Agencies (Kliatchko, 2008). Kliatchko (2008) also argue tha IMC is an audience-driven business process to strategically manage the stakeholders, content and channels in relation to the company’s brand communication.
Therefore in the case of B2B companies, IMC could be of great benefit by using the unified communication tools to leverage the targeted customer’s insight. Mangold (2009) argued that it is necessary to combine the traditional promotion mix with the newly emerged digital media in communication to perform successful marketing integration.
2.4 Customer-perceived value
In a customer-driven market, products and services are developed based on a customer’s needs and wants. Therefore in order to meet a customer’s criteria or expectations, it is important to understand the customer-perceived value, which is the difference between the benefit and all the marketing cost perceived by the customer with the comparison to its competitors. For instance, some customers, they are more sensitive to price, while others take quality as most vital element to consider when making purchasing decisions.
Hence the designing of the market strategy should be in align with its competitive advantage and display the customer-perceived value (Kotler and Armstrong, 2012).
2.5 Market Vision
When a highly innovative technology is deployed into a business, there is a big uncertainty about how the emerging technology can be efficient to the product or the production. Hence, this drives companies to always have and know its market vision which is “the ability to look into the future and picture product and services that will be successful” and it should be considered if firms wish to engage in innovation (Trott, 2012, p. 62). Market vision evaluates resources and identifies capabilities that a company has with respect of the present and future market needs, and vision a market offering that a customer is interested in (Trott, 2012).
2.6 Technology and knowledge transfer
Technology transfer is the process by which technology developed for one purpose is communicated and shared to others in the market or in the company internally and thus available to be utilized in a different application or by a new user. Therefore magnifying closer into the term, it involves the movement of ideas, knowledge and information from one context to another (Trott, 2012). Hence in relation to AR, as it is a newly emergent technology, it is becoming trendier as more companies are realising the potentials of the solution and adopting it in their organization for further development.
On the other hand, businesses are also cautious or do not have the required knowledge to adopt the solution. Therefore knowledge transfer is the result of information being recognised and used by individuals or organizations which results in actions and skills for instance projects, processes, products and more to improve performance (Trott, 2012).
Figure 1. Conceptual framework of inward technology transfer (Trott, 2012)
Technology transfer or inward technology transfer is a series of complex interactive processes presented through the conceptual framework above. The framework is a useful tool to analyse the notion of technology and knowledge transfer. The access to and the mobility of the technology information is crucial and these two factors are stressed and given most effort. However, it is a firm’s overall ability to be aware of, to identify and to take effective advantage of technology is just as paramount and it is referred to as ”receptivity” (Trott, 2012). To break down the sub-processes in the receptivity:
- Awareness: the organization scans for and discovers what information is available on technology
- Association: the organization recognizes the values and potential benefits of the discovered knowledge and technology (ideas) for the organization
- Assimiliation: the organization communicates and shares these ideas internally within the organization system and creates genuine business opportunities - Application: last but not least the organization applies the technology and
knowledge for competitive advantage.
2.7 Experiential marketing
With the combination of growth in information technology, digital innovation and the internet, the traditional marketing is shifting towards what is now called experiential marketing (Schmitt, 1999). In the present marketplace, it is all about moving away from traditional “features-and-features” marketing towards creating experiences for
customers. Through the efficient use of sensory, affective, creative and cognitive, physical, behaviours and lifestyles, and social-identity experiences, experiential marketers are able to appeal to the customers. There are four elements to experiential marketing and these are (Schmitt, 1999):
1. A focus on customer experiences
a. Experiences provide sensory, emotional, cognitive, behavioural, and relational values that replace functional values.
2. A focus on consumption as a holistic experiences
a. Examining the consumption situation and sketching the boundaries of categories and competition accordingly amounts to a radical shift in thinking about market opportunities.
3. Customers are rational and emotional animals
a. Customers are both emotional and rational human beings. Meaning that, even though customers frequently engage in rational decision-making, they are just as frequently driven by emotions, because consumption experiences are often if associated with “wants” are mostly directed towards the pursuit of fulfilling fantasies, feelings and hedonistic pleasures.
4. Methods and tools are eclectic
a. There is not one way of carrying out the Experiential, hence it is eclectic.
They are customized for certain situation or campaigns at hand meaning very ideographic. It does not provide the same standard format for all respondents.
2.8 Resource-based view model
With the help of this model companies acknowledge resources as the key to superior firm performance as it can be controlled and provide stable directions in the market (Trott, 2012). Especially, it is believed that resources enable a company to gain and sustain competitive advantage if the resources exhibits attributes that are considered as valuable, rare, imperfectly imitable and non-substitutable (VRIO). Hence to obtain a superior competitive advantage to differentiate itself from the competitors companies should focus on their internal capabilities and resources (Rothaermel, 2012). In this case, AR can be evaluated as an internal resource to maximize marketing performance, operational performance and used as a strategic competitive advantage.
2.9 Augmented Reality
2.9.1 Definition of augmented reality
Augmented reality has formally been defined in the 1997 by Azuma (1997, 2001) and is made up of three characteristics that are listed below:
1. Combines real and virtual 2. Is interactive in real time 3. Is registered in three dimensions
What is meant with “combines real and virtual” is that it would appear to the user that
what he sees as virtual objects will be co-existing or as part of his real environment (Azuma, 1997). Therefore as the combination of the real and virtual objects are in the same space and time, it is interactive in real-time. Lastly, the objects are combined in three dimensions, making the virtual objects as if they were real this is because our physical environment is three-dimensional (Azuma, 1997).
2.9.2 Applications of augmented reality
In order to use AR, there are certain tools and devices a user must have, such as (Kleef et al, 2010):
- Smart devices, such as mobile phones or tablets with in-built cameras - A standard computer with webcam.
- A head-mounted displays, such as glasses and head sets.
- A games console with camera accessory.
- A large tv with screen with advanced Set top box and webcam.
With these devices, a company can use AR in events, conferences, brochures, online campaigns, trade shows and etc. (Hidden Creative, 2013). For instance, in order to make a normal product brochure “come alive”, the user or the customer can be given a tablet, on which the AR application is installed. And when the user opens the AR application on the tablet and holds the tablet over the brochure, the AR application registers the code on the brochure and visualizes the product in 3D in real-time on the screen of the tablet.The user can interact with the 3D product visualization by moving the tablet in different directions and positions, as well as touching the screen of the tablet to interact with it. This concept applies for all the tools and devices, whether AR is accessed through smart glasses or smart phones, the way AR functions and operates is the same with its three characteristics (Kleef et al, 2010).
2.10 Technology acceptance model
AR is defined as an emerging technology in the market, therefore in order to integrate AR in B2B, it is important to look at how the companies (users) will be willing to accept and use the technology. To gain an understanding of their decision criteria and motivations behind these, the technology acceptance model (TAM) is commonly used.
TAM was introduced by Davis in 1986, it has become a well-established model for
predicting user acceptance of a new technology (Davis et al, 1989). TAM answers the question of what makes people adopt or reject a technology. The model illustrates that when an user is presented with a new technology, there are main two factors that influence their evaluation process (Davis, 1986):
1. Perceived usefulness (PU): how the users perceive a particular system would benfit the performance of the goal or strategy.
2. Perceived ease-of-use (PEOU): user’s perception of how easily accessible the system is.
2.10.1 Unified theory of acceptance and use of technology
It is also a technology acceptance model that show the user intentions to use an
information system and the user’s usage behaviour (Venkatesh et al, 2003). This model contains four key variables to determine the user’s acceptance of the technology (Kleef et al, 2010):
1. Performance expectancy 2. Effort expectancy 3. Social influence 4. Facilitating conditions
In his later study with Venkatesh, Davis (2000) has also proposed that social influence also acts as a determinant variable that have a direct effect on a user’s intentions to use a new technology. Social influences are characterized as subjective norms that along with personally held attitudes towards a technology can influence and predict a user behaviour (Shen et al, 2006).
3 Methodology
To carry out a research study, the authors first, plan and produce a set-up proposal to guide their research every step of the way to study the topic of interest and fulfil the purpose of the study (Creswell, 2014). Hence once again, the purpose of the study is to:
“ identify if AR as an emerging tool is able to communicate information efficiently from commercial and non-commercial aspects in B2B sector”.
Depending on the nature of the research problem or topic of interest, there are different approaches one could follow. A research approach is made up of procedures of inquiry, which is the design of the research and lastly, it contains specific research methods, to collect, analyse and interpret the data (Creswell, 2014). It is also important to make sure that the research is valid therefore quality criteria is also applied. Hence there are four crucial elements to establishing the foundation of a successful research study and they will be illustrated further in this chapter as:
1. Research approaches 2. Research design 3. Research method 4. Quality criteria
3.1 Research approach
3.1.1 Inductive vs. deductive research approaches
For this research work, by looking at the nature and context of the topic in interest, the authors carefully evaluated the two general approaches to reasoning, which are
inductive and deductive reasoning. With deductive nature of research, authors study the already existing theoretical considerations around a particular domain (with option could form a hypothesis) which is then put into empirical observations to test the relationship between the theory and domain (Bryman and Bell, 2015). In contrast, inductive reasoning is a building process, where theories and concepts emerge from empirical data and observations of specific real life situations (Hyde, 2000; Oghazi, 2009). Hence in order to fulfil the purpose, the collection of the accurate empirical data
was guided and based on deductive reasoning with pre-existing established theories and concepts.
3.1.2 Quantitative and qualitative research
As there have not been many previous studies conducted in the area of this topic in interest, the authors chose the qualitative approach. The authors wanted to get an in- depth and meaningful insight into the implementation of augmented reality in B2B industry to uncover the current use and effect of this booming technology on the market and conclude patterns and norms.
On the other hand, as quantitative research approach focus on numbers and quantifying the collection and analysis of hard and structured data from large and representative population, it did not fit with the purpose of this research study (Bryman and Bell, 2015). Whereas the qualitative approach was more suitable, given that it produces a rich amount of detailed data and focuses on interpreting complex insights of real life
phenomenons and issues in their natural settings (Hyde, 2000; Oghazi, 2013). There are more contrasting factors between quantitative and qualitative research which is shown on Table 1. below, and it is also possible to combine both two approaches.
TABLE 1.
Some common contrasts between quantitative and qualitative research (Bryman and Bell, 2015, P416)
QUANTITATIVE QUALITATIVE
Numbers Words
Point of view of researcher Point of view of participants Researcher distant Researcher
Theory testing Theory emergent
Static Process
Structured Unstructured
Generalization Contextual understanding Hard, reliable data Rich, deep data
Macro Micro
Behaviour Meaning
Artificial setting Natural setting
3.2 Research design
There are three main designs that can be used to carry out a research process. If the purpose of the research is to gain insights and understanding of a problem or situation, then exploratory design is the most suitable choice to go with (Malhotra, 2010).
However if the study aims to identify and describe characteristics or functions of how something works, such as a market, the descriptive design is the one to adopt (Malhotra, 2010). The third and last research design is causal research, which is used to study the relationship between cause and effect through experimentations (Malhotra, 2010). The detailed comparison between these three research designs are illustrated further in Table 2.
TABLE 2.
A comparison of basic research designs (Malhotra, 2010, p. 104).
EXPLORATORY DESCRIPTIVE CAUSAL Objective Discovery of
ideas and insights
Describe market characteristics of functions
Determine cause and effect relationships Characteristics Flexible and
versatile Often the front end of total research design
Market by the prior formulation of specific hypotheses Pre-planned and structured design
Manipulation of one or more independent variables Measure the effect on dependent variables Control of other mediating variables Methods Expert surveys
Pilot surveys, case studies Secondary data:
qualitative analysis Qualitative research
Secondary data:
quantitative analysis Surveys Panels
Observation and other data
Experiments
The authors applied combination of both exploratory and descriptive research designs in this study. First of all, the purpose of the study was to get an in-depth knowledge and understanding about the use of AR in the B2B market and then describe the
characteristics of this technology and determine the current perceptions around AR.
Hence in detail, the authors carried out an exploratory research and applied a cross- sectional research design which is part of the descriptive research design, although it is used more in quantitative studies, it could be utilized in qualitative research approach as well. With this research design, the focus is on attaining variation and it is established by observing more than one case (Bryman and Bell, 2015). However unlike the
quantitative research approach, in qualitative study, it is not carried out at a single point in time, where the data is not collected simultaneously. This design is applied in forms of qualitative interviews with semi-structure with the combination of narrative and phenomenology features. The narrative and phemenology features study and describe social situations and specific phenomenons to provide conclusions which account for each particular case (Creswell, 2014; Oghazi et al, 2012). In this research work, as AR is a newly emerging technology and creating a great buzz in the market, the authors perceived this event as a phenomenon and therefore studied it to get a further understanding of what AR is and its use in the market.
3.2.1 Research strategy
When choosing a research strategy, there are three conditions one must consider in order to choose the fit one as there are several different strategies. The first factor to evaluate is the type of questions that are asked in the research, secondly, how much control a researcher has over the events taking place under the study and lastly, the degree of focus on contemporary events in comparison to historical events (Yin, 2014).
Hence depending on the answers to these three conditions, a researcher can choose between experimental, survey, archival analysis, history and case study strategy which are illustrated in Table 3 (Yin, 2014). Furthermore, Ghauri and Grønhaug (2005) states that experimental and survey researches have quantitative nature whereas historical, archival analysis and case studies lie on the qualitative spectrum with explanatory, descriptive and exploratory elements. Hence, as this study was based on qualitative nature, as well as the two research questions explores the “how” aspects of AR and as it is a contemporary event with little or no requirement to control the behavioural events, the authors chose the case study strategy as a fitting approach for this thesis work.
Moreover as the authors wanted to study the performance of AR and produce results that can be applicable across different industries within the B2B sector, a multiple case study was conducted.
To highlight further, a single case study has a holistic approach with embedded units which allow the researcher to study a case in depth and with focal concentration as the case is considered unique and critical (Baxter and Jack, 2008). On the other hand, with a multiple case study, several holistic cases are studied in order to understand and analyze events within each sitting of the cases and across them to identify the similarities and contrasts (Yin, 2014). The advantage of conducting a multiple case study is that it is considered rather compelling and robust as it is validated through the replication logic (Baxter and Jack, 2008). For instance, in order to ensure the finding of a significant event, a second and more studies are conducted to replicate the finding or further identify contrasting results (Yin, 2014). However, it can be very time-consuming and require superior resources and capabilities that can be of limitations to the researcher (Yin, 2014). Therefore, even with the consideration of the disadvantages, the multiple case study has allowed the authors to carry out the qualitative study with exploratory and descriptive approaches through semi-structured interviews with five companies.
3.2.2 Research sources
The authors used both primary and secondary data for the research study. Before the collection for primary data was undergone, the authors gathered secondary data to identify the purpose of the study and better define the problem discussion. It was also used to develop an approach or a strategy to tackle the problem discussion and the research questions. Hence secondary data is previously collected data and already existing in the store of social knowledge and it is for some purposes other than the
TABLE 3.
Relevent situations for different research methods (Yin, 2014)
Method Form of
research question
Requires control of behavioural events?
Focuses on contemporary event?
Experiment How, why? yes Yes
Survey Who, what,
where, how many, how much?
no Yes
Archival analysis Who, what, where, how many, how much?
no yes / no
History How, why? no No
Case study How, why? no Yes
problem at ahand but could be of high relevance due to the the same topic of nature (Malhotra, 2010, Oghazi et al, 2009). After the secondary data collection process, the authors proceeded to primary data collection, which refers to data that is collected for the specific research problem at present (Hox and Boeije, 2005; Oghazi, 2014).
The advantage with primary data collection is that all the procedures are tailored and specifically designed to the purpose of the study and fit to answer the research questions (Hox and Boeije, 2005; Oghazi, 2013). However it is a complex process as it involves the authors into the social setting in person which can be costly and time consuming (Malhotra, 2010). On the other hand, secondary data collection is relatively less costly due to its ease of accessibility and the collection period is shorter (Malhotra, 2010). But there are limits to secondary data as well, as it was originally collected for a different purpose, it is hard to familiarize with the data and it is difficult to control the quality of the data as some of the variables can be missing (Bryman, 2008).
In this study, primary data was collected through in-depth qualitative interviews (Appendix A) with the companies that provide AR solutions to other companies and companies that use AR in their organizations. The secondary data was based on prior studies and research conducted on the topic of AR as well as background information from the homepages of the companies that participated in the study.
3.3 Data method
3.3.1 Data collection method and instruments
There are four basic qualitative data collection methods; a qualitative observation, qualitative interviews, qualitative documents and qualitative audio and visual materials (Creswell, 2014; Mostaghel et al 2012; Oghazi, 2014). For the data collection, the authors used two different methods, through conducting semi-structured qualitative interviews to attain first-hand data and lastly through reviewing qualitatative documents as secondary data source. On Table 4. it illustrates the two data collection methods in detail, in this case, the authors primarily focused on using face-to-face, in person interviews, but due to different circumstances such as geographical limitations, some of the interviews were conducted through Skype and email. As for the documents, the authors used the public documents available, such as gathering information from the homepages of the each company. Furthermore, as this is a qualitative research, the
authors were the actual key instruments examing documents and interviewing
participants for the collection of the data. For the interviews, the authors developed an interview guide or a protocol for asking questions efficiently with structure as well as recording down the answer. The authors used an audio-taping application to record the interview and at the same time made hand-written notes in case the recording equipment failed. After each interviews the authors conducted the transcriptions of the recorded information and prepared it for the data analysis.
TABLE 4.
Qualitative data collection types, options, advantages and limitations (Creswell, 2014, p. 191).
DATA COLLECTION TYPES
OPTIONS WITHIN TYPES
ADVANTAGES OF TYPES
LIMITATIONS OF TYPES
INTERVIEWS • Face-to-face interview
• Telephone – interviews by phone
• Focus group – interviews by participants in a group
• E-mail Internet interview
• Useful when participants cannot be directly observed
• Participants can provide historical information
• Allows researcher control over the line of questioning
• Provides indirect information filtered through the views of interviewees
• Provides information in a designated place rather than the natural field setting
• Researcher’s presence may bias responses
DOCUMENTS • Public documents – minutes of meetings or newspaper
• Private documents – journals, diaries, or letters
• Enables a
researcher to obtain the language and words of participants
• Can be accessed at a time convenient to researcher
• Represents data to which participants have given attention
• May be protected information
unavailable to public or private access
• Requires transcribing or optically scanning for computer entry
• Materials may be incomplete
• The documents may not be authentic or accurate
3.3.2 Operationalization
In order to define and distinguish the theories and concepts from each other and clarify the essential ones most relevant to the purpose of the study, operationalization method was used to break them down into easily understandable but detailed terms. Further, the formation of the interview questions were based and matched in accordance to these
concepts and terms to organize and create measurements relevant to the collection of the data. As can be seen on Table 5., with this process, the theories and concepts were divided into four major variables with its respective supporting sub-concepts. In unison these main and sub concepts contributed to the development framework of acquiring the empirical findings.
TABLE 5.
The Operationalization of theories and concepts CONCEPTS CONCEPT
DEFINITIONS
SUB CONCEPTS / DEFINITIONS
OPERATIONALIZATION DEFINITION
QUESTIONS Augmented
Reality (2.8.1)
1. Combines real and virtual 2. It is
interactive in real time 3. Is registered
in 3D (Azuma, 1997)
To measure the overview of how companies perceive AR to be and the applications that they offer and use
1-4
Marketing Strategy (2.2)
The marketing logic is to create value propositions and gain relationships (Kotler
& Armstrong, 2012)
• Market vision: the ability to look into the future and picture product and services that will be successful (Trott, 2012)
• Competitive advantage: offer greater value to a customer compared to the competitors (Kotler & Armstrong, 2012)
To measure the promotional aspects of using AR as a marketing tool and advantage of using AR
5-9
Technology Acceptance Model (2.9)
1. Perceived usefulness – the expectancy of AR performance 2. Perceive ease of use
- the expectancy of AR effort
3. Social influence - public perception of AR (Davis, 1989)
• User-friendliness:
a machine or a system that is easy to use or understand
• Time frame: the process of the idea to become a product or service
• Training and consulting: a company is offering or giving the customer advice or training (Oxford University Press, 2015)
To measure
usefulness / benefits of AR and how efforts free it is to use.
10-14
Challenges and future outlook
The task that test company’s abilities and what will likely happen in the future(Oxford University Press, 2015)
To measure
implementation of AR and its potentials.
15-18
3.3.3 Interview guide
As stated in the data collection method part, the authors carried out semi-structured interviews. In order to structure the interviews, the authors made an interview guide to help the process go smooth and gain valid data. Interview guides are referred to the prompts of areas that will be covered when addressing issues and questions when employing an unstructured or semi-structured interviewing (Bryman and Bell, 2011).
As King (1994) stated, an interview guide should cover the most relevant topics in an interview to aid the process of an interview and carry it out in a most efficient and reliable way. Ghauri and Grønhaug (2005) suggest a-three-step approach to preparing an interview:
1. Analyze research problem
2. Understand the needed information from the interviewee and 3. Who would provide this information
Firstly, the authors re-evaluated the research questions once again in close relation to the problem discussion and tried to understand what information and data was needed to fulfill the purpose of the study. In order to do this, the theories and concepts were re- evaluated and put into operationalization measurements to guide the formation of the questions that will be used in the interviews. The interview questions were based on the four main concepts in the operationalization (3.3.2) and included open-ended questions to probe and attain further insights. Hence the interview plan was semi-structured and the questions were pre-tested and approved by two supervisors in the academics at Linnaeus University before officially conducting the interviews.
Third and lastly, we sampled the relevant participants for the study after a careful market research and formulated an information sheet to let the participants know the purpose and procedure of the study. Before the initial contact with the sampled
participants, the authors took several factors under consideration, such as the time frame
of the interviews, incentives to the participants as well as cost of travelling and etc. As recommended in Burke and Miller’s study (2001), appointments with the sampled participant companies were scheduled after contacting them through phone and email and the information sheet was included in the email together with contact details of the authors. The authors prepared for the interviews by studying the background of the each company in detail and reviewing the interview questions. As Ghauri and Grønhaug (2005) suggest taking notes and recording the interview, the authors also prepared the audio-taping application and its functions were tested before hand. Aside from this memos were used to note down the reflection and thoughts from the interview sessions.
The beginning of the interview was opened with simple introduction questions, which created an easy start to the conversation about the main topic; augmented reality. The next stage followed with asking questions based on the four operationalization concepts;
AR, marketing strategy, TAM, the challenges and the future outlook of augmented reality. Towards the end, the interview focused on phasing out in a positive and tranquil way in order to give the participant the opportunity to give further comments on the subject as advised by King (1994). The duration of the interviews were between thirty minutes to one hour each, except for one interview which was carried out through e- mail.
3.3.4 Sample selection
Sampling approaches can be divided up into two broad categories: probability and non- probability samples (Ghauri and Grønshaug, 2005; Oghazi et al, 2012). In probability samples each unit of sample is selected through random selection but in non-probability sampling, the samples are selected with purpose and strategy. Therefore for the purpose of this study, the non-probability sampling was used and there are four types of this sampling (Ghauri and Grønhaug 2005; Shah et al 2010):
1. Convenience sampling is units that one would find most convenient and accessible.
2. Judgment sampling is to select units that are representative of the population based on judgments or knowledge.
3. Quota sampling is making sure of that certain subgroups of units are represented in the population.
4. Purposive sampling is to sample cases and participants in a strategic way relating to the research questions. There are two examples of purposive sampling in qualitative research: theoretical sampling and snowball sampling (Bryman and Bell, 2015).
a) Theoretical sampling ‘is the process of data collection for generating theory whereby the analyst jointly collects, codes, and analyzes his data to collect next and where to find them, in order to develop his theory as it emerges. The process of data collection is controlled by the emerging theory, whether substantive or formal.’ (Bryman and Bell, 2015; Glaser and Strauss, 1967, p.
45). This emphasize that it is an ongoing process.
b) Snowball sampling is the process where the researcher takes contact with a small group of people who are relevant to the study, and by gaining contact with people it establish new contacts.
In this study the participants were selected through the purposive sampling which means that the companies were sampled strategically in order to be relevant to the research study (Collingridge and Gantt, 2008). Further a snowball sampling technique was used as part of the purposive sampling as it is widely used when choosing a qualitative approach, especially when trying to collect data from ‘hidden populations’
(Noy, 2008). Also the significance with a snowball sampling is that the authors make initial contact with a small group of representatives who are relevant to the nature of the topic and then uses these to establish a network and contact more relevant subjects (Beheshti et al, 2014; Bryman and Bell, 2015). After selecting the sampling technique, the authors searched for relevant companies to contact, however there were a limited amount of companies in Sweden that had applied AR as a part of their production or as a marketing tool. Moreover, several industries were considered in order to increase the responses and interviews which additionally made the industry aspect broad. Therefore, the authors decided to contact companies outside of Sweden, and search within the European countries. Once the participants were selected based on their market
experience of AR and knowledge of the topic under study, the authors created a list of companies that either provided or operated with AR (Appendix C). The companies were contacted through telephone and/ or e-mail and five companies agreed to participate in interviews for this study and the details of all the five companies can be seen on Table 6. below. Four of these companies were providers of AR, and one company was a user of AR.
TABLE 6.
Companies participated in the study.
COMPANY NAME COMPANY BACKGROUND CONTACT PERSON Animech Technologies Swedish based company that
was founded in 2007 and specialize in software solutions and 3D modeling.
Staffan Hagberg, Business manager
Hidden Creative British based company, who is working with digital marketing that specialize in technologies such as augmented reality.
Matthew Trubow, CEO
Intertisement Danish based company, who is developing innovative
interactive application and pioneers in the field of
customized Augmented Reality solutions.
Kim Bleshøy Nielsen, Managing director & partner
Volvo Group Swedish based company, one
of the leading manufacturers of trucks, cars, construction equipment, and marine and industrial engines.
Christer Lundevall, Specialist in simulation technology
Guillaume Favreau, Business innovation manager
XMreality Swedish company founded in
2007 and specializes in developing and offering remote guidance solutions based on augmented reality to industrial businesses.
Niklas Rengfors, Sales manager
3.3.5 Data analysis method
Data analysis is about using specific strategies to transfer the raw material into an organized structure that is being studied (Mostaghel et al, 2015; Thorne, 2000). In the study, Creswell’s (2014) 6 steps data analysis process was used to analyze the data as a general guide with the combination of the operationalization. The outline of this data analysis can be seen on Figure 1 and each 6 steps are elaborated below.
Step 1: The data from the interviews were gathered and transcribed; in this step, three interviewers recorded the data individually and then combined the data into one document in order to gain a holistic sense of information.
Step 2: Reviewing all the data.
Step 3: Started coding all of the data into themes. The data was segmented and
categorized under the four main concepts of the operationalization (Table 5.). They are 1. AR, 2. Marketing strategy 3. TAM and 4.Challenge and future outlook. Hence in this case, predetermined codes were used to fit the data.
Step 4: The sub-concepts under the major themes were elaborated further.
Step 5: All the themes and sub-concept were put together to provide advanced
description of the data through narrative and phenomenological approach by analysing the significant statements and responses.
Step 6: Based on the themes, the empirical data from each participant companies were compared against each other and further interpretations were made by the authors to conclude the results.
Figure 2. Data analysis in qualitative research (Creswell, 2014)
3.4 Quality Criteria
In order to conduct the research study in an accurate and precise way, the quality criteria need to be considered when designing and implementing the study. Validity and
reliability are two important indicators in measuring the quality of a qualitative study.
Interpreting the meaning of themes / descriptions Inter-relating themes / description
Themes & Description Coding the data (hand or computer)
Reading through all data
Organizing and preparing data for analysis Raw data (transcripts, fieldnotes, images, etc.)
As Morse et al. (2008) argued, validity is to ensure the plausibility and credibility of the evidence used in a study in relation to its prospective findings or conclusion.
3.4.1 Content validity
Content validity examines whether the measure reflects the construct in both content and scope (Johnston et al. 2014, p. 241). In other words, the content validity is to test whether the questionnaire designed is adequate to cover the research questions in the interview. In the study, the conclusion of the research was conducted by applying the four main variables, AR, marketing strategy, TAM, challenges and future outlook. The group panel discussed and assessed the usefulness and essential for each interview questions in order to reach the purpose. Two interviews were conducted through face- to-face interviews, the other two interviews were conducted through Skype, an online media, while the last one was conducted through email. This was due to factors such as distance, time limitation, and cost. Before the interviews, the questions were practiced, edited and re-formulated, in order to avoid misunderstandings and to get the required results. In addition, in order to make it validated, once the interview questions were formulated, it was pre-tested by professionals in the marketing field as well as academics at Linnaeus University.
3.4.2 Construct validity
Construct validity identify the accurate relationship between the operational measures and the concepts being studied (Yin, 2014). This means to test all the measurements and variables that are set up for the study and validate them. By defining the research topic in terms of the specific concepts, and identifying operational measures to match the concepts, the construct validity can be tested (Parida et al 2014; Yin, 2014). In this case, the study has reached the construct validity with the operationalization procedure
(3.3.2).
3.4.3 External validity
External validity refers to the degree to which the conclusion from the specific research can be generalized and applied across social setting, which is an important element to consider when assessing the validity of the study (Bryman, 2008). The tendency of the qualitative study is to provide a considerable descriptive detail of a specific situation in
the context of social settings; therefore it is necessary to think from a realistic
perspective of the social behaviour or attitude to give contribution to practice (Bryman, 2008). The specific situation focused in this study was to identify if AR as an emerging tool is able to communicate information effectively (easier to communicate and
understand) from commercial and non-commercial aspects in B2B sector. The four main concepts that guided the research process provided realistic yet general
perspective of the social market of AR thus the results from this study is valid and can be applied to social settings.
3.4.4 Reliability
Reliability refers to the content to which the data collection technique or the analysis can be repeated to yield the same result (Saunders et al, 2007). A way to ensure the reliability of the research is to examine the indicators of stability, internal reliability and inter-observer consistency (Bryman 2008; Oghazi and Philipson, 2013). In all
interviews, three authors involved to collect the data, so that to reach the triangulation (Yin, 2014). In addition, the transcripts from the interviews were reviewed during the process of the analysis and conclusion, which is to make sure there is not obvious mistakes derived from the data collection, to make the study repeatable.
