Media Management Master Thesis 2015 by Sondra Duckert

MEDIA AS A BROKER : HOW MEDIA CONVERGENCE IN COLLABORATIVE CONSUMPTION IS CHANGING THE ACCOMMODATION INDUSTRY

Fourth Semester Master Thesis January 6, 2015 Opera;ons and Innova;on Management -‐ Media Management Aalborg University -‐ CPH

Supervisor: Henrich Dahlgren Authors: Elena-‐Andreea Manole, Sondra Lynell Duckert and Sophie Malene Jørgensen

Image source: http://www.shareable.net/blog/stanford-collaborative-consumption-event-big-business-and-the-little-guy-in-the-same-room

EXECUTIVE SUMMARY The Internet, social media networks, wireless technologies, and mobile apps are fuelling the growth of Internet based peer-‐to-‐peer (P2P) marketplaces. Collaborative Consumption (CC) is one such area where consumers are embracing the idea and convergence of these innovative technologies as they are able to share products and services with others using P2P marketplaces. With the backing of media technologies, the essence of CC is thus based on sharing, trust between strangers, and interactions that facilitate the creation of online knowledge communities. This case study therefore explores and analyses the role of ‘media as a broker’ within CC companies of online hospitality services such as Airbnb, in comparison with traditional ones in the accommodation industry in Denmark. Building on the uses of CC and its applications a research strategy of document analysis is used in order to frame its relationship to media technologies in the context of the accommodation industry. The research around the main question, ‘What is the perceived value of peer-‐to-‐peer collaborative consumption from the consumers’ perspective and how can traditional players in the Danish accommodation industry take advantage of it and regain market share?’ as well as two sub-‐questions, takes both a quantitative and qualitative approach to the study. Supporting this approach is the combination of three different theories that are effectively mapped out in a theoretical framework used to conceptualise the main points revolving around answering the research questions: the theory of Convergence Culture helps to recognise how media technology is transforming consumer behavior in relation to the characteristics of the CC phenomenon; the diffusion of innovations model is used to help identify perceived value of consumers and innovations; and the Disruptive Innovation theory helps to explain in what ways CC companies are disrupting the accommodation industry. The analysis accordingly represents how CC companies use of media technologies play a stronger role in the formation of online communities thus propelling the acceptance of the phenomenon within the accommodation industry in Denmark. The results also indicate how interpersonal channels contribute to the spread of CC with the use of P2P technology as well as their most shared attributes and values, thereby shifting the decision-‐making process of the new consumer. The findings also suggest that the disruptive technology of P2P, as a business model, introduced new methods of offering value propositions to consumers. Moreover, with the aim of offering practical suggestions for the traditional accommodation sector the research contributes a way of identifying and constructing new possibilities for engaging consumers on a more personal level, in their attempt to regain market share.

TABLE OF CONTENTS CHAPTER 1. INTRODUCTION ............................................................................................................................. 1 1.1. PROBLEM FORMULATION ................................................................................................................................................. 3 1.2. REPORT BREAKDOWN ....................................................................................................................................................... 5 1.3. DELIMITATIONS .................................................................................................................................................................. 5 CHAPTER 2. THEORIES ........................................................................................................................................ 7 2.1. THE THEORY OF CONVERGENCE CULTURE ................................................................................................................... 7 2.1.1. Collective Intelligence ............................................................................................................................................... 8 2.1.2. Participatory Culture ................................................................................................................................................ 9 2.1.3. Media Convergence ................................................................................................................................................. 11 2.2. THE THEORY OF DIFFUSION OF INNOVATIONS .......................................................................................................... 12 2.2.1. Elements Within the Innovation-‐Decision Process .................................................................................... 14 2.3. THE THEORY OF DISRUPTIVE INNOVATION ................................................................................................................ 17 2.3.1. Disruptive Innovations ........................................................................................................................................... 18 2.3.1.1. Sustaining and Disruptive Innovative Technologies ............................................................................................................. 19 2.3.1.2. New Market and Low-‐End Disruptions ...................................................................................................................................... 20

CHAPTER 3. METHODOLOGY .......................................................................................................................... 22 3.1. RESEARCH DESIGN ........................................................................................................................................................... 22 3.2. METHODOLOGICAL APPROACH ..................................................................................................................................... 25 3.2.1. Exploratory Study .................................................................................................................................................... 25 3.3. DATA COLLECTION .......................................................................................................................................................... 26 3.3.1. Primary data .............................................................................................................................................................. 27 3.3.1.1. Sampling Frame and Stratification ............................................................................................................................................... 28 3.3.1.2. Justification of Converging Media Technology Research Choices ................................................................................... 30

3.3.2. Secondary data .......................................................................................................................................................... 31 3.4. RELIABILITY AND VALIDITY ........................................................................................................................................... 32 3.5. LIMITATIONS ..................................................................................................................................................................... 33 CHAPTER 4. ANALYSIS ...................................................................................................................................... 36 4.1. CONVERGENCE CULTURE ANALYSIS OF COLLABORATIVE CONSUMPTION ............................................................ 38 4.1.1. Collaborative Consumption Explained Through Convergence Culture Theory ............................ 41 4.1.1.1. Collective Intelligence ........................................................................................................................................................................ 41 4.1.1.2. Participatory Culture .......................................................................................................................................................................... 44 4.1.1.3. Media Convergence ............................................................................................................................................................................. 45

4.1.2. Convergence Culture Analysis Takeaways .................................................................................................... 50 4.2. DIFFUSION OF INNOVATIONS ANALYSIS ...................................................................................................................... 52 4.2.1. Knowledge -‐ The Social System Variables of Collaborative Consumption ...................................... 52 4.2.1.1. Characteristics of Collaborative Consumption Adopters .................................................................................................... 54

4.2.2. Persuasion -‐ The Perceived Values of Collaborative Consumption .................................................... 57 4.2.3. Decision -‐ Adoption or Rejection of Collaborative Consumption ........................................................ 62 4.2.3.1. Rate of Adoption of Collaborative Consumption in Denmark ........................................................................................... 65

4.2.4. Diffusion of Innovations Analysis Chapter Takeaways ............................................................................ 67

4.3. DISRUPTIVE INNOVATION ANALYSIS ............................................................................................................................ 69 4.3.1. Comparison of the performance trajectories ............................................................................................... 69 4.3.2. Collaborative Consumption’s Disruption on the Danish Accommodation Industry ................... 70 4.3.3. Actual Market Share Loss in Traditional Danish Industry ..................................................................... 74 4.4. SUGGESTIONS FOR THE TRADITIONAL PLAYERS ........................................................................................................ 76 4.5. DISRUPTIVE INNOVATION ANALYSIS TAKEAWAYS .................................................................................................... 79 CHAPTER 5. CONCLUSION ................................................................................................................................ 81 REFERENCES ........................................................................................................................................................ 84 APPENDICES ......................................................................................................................................................... 93 APPENDIX I -‐ AIRBNB EMAIL CORRESPONDENCE .............................................................................................................. 93 APPENDIX II -‐ ESTIMATION OF TOTAL AMOUNT OF OVERNIGHT STAYS FOR CC COMPANIES .................................. 94 APPENDIX III -‐ HOSTEL ROOM CAPACITY ........................................................................................................................... 95 APPENDIX IV -‐ NUMBER AND CAPACITY IN THE DANISH ACCOMMODATION INDUSTRY ........................................... 97 APPENDIX V -‐ MEDIA TECHNOLOGIES IN CC COMPANIES ................................................................................................ 99 APPENDIX VI -‐ MEDIA TECHNOLOGIES IN TRADITIONAL ACCOMMODATION COMPANIES ..................................... 103 APPENDIX VII -‐ COST SAVING COMPARISON CHART ...................................................................................................... 107 APPENDIX VIII -‐ GROWTH IN AMOUNT OF CC COMPANIES IN DENMARK ................................................................. 108 APPENDIX IX -‐ GROWTH OF CC USERS BY AVAILABLE ROOMS IN DENMARK ........................................................... 108 APPENDIX X -‐ GROWTH OF CC MEMBERS IN DENMARK ............................................................................................... 109 APPENDIX XI -‐ CC GROWTH BY OVERNIGHT STAYS IN DENMARK .............................................................................. 109 APPENDIX XII -‐ CALCULATING THE RATE OF ADOPTION .............................................................................................. 110 APPENDIX XIII -‐ TOTAL AMOUNT OF OVERNIGHT STAYS AT HOTELS AND HOSTELS IN DENMARK ..................... 111 APPENDIX XIV -‐ CALCULATING THE MARKET DISRUPTION ......................................................................................... 112 APPENDIX XV -‐ ACCOMMODATION INDUSTRY OVERNIGHT STAYS IN 2012 ............................................................. 113

CHAPTER 1. INTRODUCTION Â The changing dynamics within the accommodation industry have brought forward a new competitor to the traditional accommodation companies - the online collaborative consumption (CC) companies. Startling numbers from the alternative accommodation sector revealed that one of the most popular providers had over 800,000 listings in 192 countries and 10 millions stays in 2013 (Airbnb no. 1, 2014). This number pales in comparison to the traditional (overall) hotel market yet their immense popularity has not gone unnoticed considering that Hilton Worldwide operates 610,000 rooms in 88 countries (Travlpeer, 2014). Highlighting this fact is not to diminish Hiltonâ&#x20AC;&#x2122;s growth success but only to show that what Hilton has built in 93 years, Airbnb has done in four (Botsman, 2014). Furthermore, a report of recent losses of 0.05% of quarterly budget hotels revenues [hotels that offer fewer services and amenities] was attributed to the rise in the alternative accommodation sector (Zervas et al., 2014:3-4). The study represents data surrounding the impact of the alternative accommodation provider, Airbnb, its rapid growth, and perceived disruption against traditional lower-tier hotels.

Figure 1 - Hospitality Financial and Tech Professionals Conference (Botsman, 25 June 2014) Under these circumstances, this rapid rise in the alternative accommodation sector is adding to the discourse within the traditional accommodation industry including heated debates regarding lobbying 1

for better regulation and taxation by local municipalities, where traditional hoteliers would like to see a level playing field for all in the industry. However, this also provides evidence that hoteliers may in fact consider this new accommodation sector as competition, as one hotelier expressed, "They're a competitor, and what we have in common with them is that guests are experiencing our cities, there’s always going to be a different way of doing it.” (HNN, 2014:24). If hoteliers are able to defeat the alternative accommodation sector through legislation and lobbying, tourism researchers fear that they may miss an enormous opportunity to create any transformations within the industry (MIT Sloan EE, 2014). Moreover, the issue with traditional hotels is that their reactions to the alternative accommodation sector are more in line with marginalizing this new paradigm instead of learning from them. For this reason, it is equally important to understand the factors behind what is happening within the accommodation sector. In other words, factors that have facilitated the sudden rise in the alternative accommodation sector and what is assumed by some experts to provide an advantage over traditional providers is the combination of innovative technology, close knit communities, trust among strangers, and altruism (Hamari et al., 2013:5). These factors, and others, characterise a phenomenon known as ‘collaborative consumption’. CC refers to the sharing of products and services between ordinary people and points to a trend in the changes in modern consumer behavioural needs (Botsman and Rogers, 2011:217). The phenomenon of CC is based on a model of trust and is commonly predicated by the use of peer-to-peer (P2P) network technology that helps to bring a different dimension to online marketplaces. The basics behind any P2P platform is taking assets that are no longer useful to some individuals and sharing them with other individuals in exchange for a fee. This is the underlying basis on which many accommodation rental websites such as Airbnb, Roomorama, and HomeAway work, where "that idling capacity of underused goods is redistributed and individuals can make money from belongings that previously just sat idle" (Botsman and Rogers, 2011: 106). In this way, sharing becomes convenient, secure, and more effective than ownership. The use of P2P technology, an approach by which digital content is distributed and brought on by the proliferation of social networks, smartphones, wireless technology, etc., (Pick, 2012:5) acts as an intermediary in the process of exchanging things online: “Technology now allows for a variety of transactions between ordinary consumers by finding equilibrium between time and money, supply and demand. Transactions once locked up and never realised now create entirely new economies, free of established brands and fat middlemen" (Shah, 2011). CC is about learning how to create value out of shared and open resources

in ways that balance personal self-interest with the good of the larger community (Botsman and Rogers, 2011:69). Participants in the alternative accommodation sector are a community of passionate users who appear willing to offer their guests a more authentic and cost saving experience than traditional hotels. By the same token, the traditional accommodation industry has been slow in transitioning into using current innovative technologies differently that could lead to offering genuine value for their customers. For example, it is now recommended that hotels websites be structured differently to avoid losing out to mobile device users (O’Mahony, 2014). Not to mention that hotel guests today are more apt in volunteering personalized information in order to get an experience that is unique to them: “Travellers want control of their own itineraries tailored to their priorities (…). A personalized and thoughtful technological experience will set the bar for great hospitality that will be defined in the near future” (Coleman, 2013). In contrast, some within the traditional industry continue to adhere to out-dated customer expectations such as providing dated amenities (Trivett, 2013) e.g. breakfast bars and Wi-Fi connectivity. On a larger scale, a different reaction to the CC phenomenon has been observed within traditional companies, where their response is to buy the CC companies instead of competing with them. A relevant example is in the car rental business, where Avis bought car-sharing company Zipcar (Eisenstein, 2013). This has not yet happened within the accommodation industry, but it is of great relevance to this study, as the report will generate a different approach that can be set in motion by traditional accommodation companies in their pursuit to compete with CC companies.

1.1. Problem Formulation This study will focus on the accommodation industry in Denmark, taking the innovation of P2P CC as a case study. When looking at the accommodation industry in Denmark, there are approximately 54,833 hotel rooms in 958 hotels that are available for the tourism market. Comparatively there are around 80,005 listings of available rooms in Denmark that are not provided by the traditional accommodation industry but offered through online marketplaces, such as Airbnb, HomeExchange, and Roomorama. With such a large number of marketed rooms available for renting or sharing there is little skepticism that traditional hotels are beginning to see this new alternative accommodation sector as a likely prospect.

Accordingly, the report focuses on exploring the trend of P2P CC within the accommodation industry, where media plays the role of intermediary between peers. The phrase ‘media as a broker’ is used to convey how and why CC can even exist and how innovative technologies converge to develop new platforms of communication and commerce. By using Rachel Botsman definition of CC "an economic model based on sharing, swapping, trading or renting products and services enabling access over ownership" as a foundation, this study seeks to identify various traits within the CC movement and their connection to online media use. Thus investigating how the innovations within CC have been adopted by the mainstream consumers and have disrupted traditional businesses. For this, one main research question has been formulated along with two sub-questions that have the purpose to guide and maintain the focus of the study throughout the research and analysis. Main research question: What is the perceived value of peer-to-peer collaborative consumption from the consumers’ perspective and how can traditional players in the Danish accommodation industry take advantage of it and regain market share? 1. What converging media technologies used in peer-to-peer collaborative consumption are creating perceived customer value and how do they differ from the established accommodation firms’ usage of media technologies? 2. How and why is the trend of peer-to-peer collaborative consumption diffusing among consumers disrupting the traditional business players in the Danish accommodation industry? The analysis will illustrate the phenomenon of how media and online businesses eliminate the traditional middleman, when exchanges are made between private sellers and buyers, thereby facilitating CC. Moreover, the result of this study will account for how media becomes the broker and anyone with an Internet connection can become a business player, as well as addressing the impact CC has on the traditional firms. By using a theoretical framework as the foundation for identifying contributing factors for the CC movement, this report will look at the Convergence Culture (Jenkins, 2006) to explain the appeal of CC in regards to the use of media technologies; Diffusion of Innovations (Rogers, 1995) to discover influences on customers perceived values, and disruptive innovation (Christensen, 1997) to find out in what ways, if any, the alternative accommodation sector is disrupting the traditional accommodation industry.

1.2. Report Breakdown The following image presents the contents and flow of this report.

Figure 2 - Report Overview (Own model, 2014)

1.3. Delimitations The following section provides details on what factors this study does not deal with in order to further specify the exact focus of the research. Due to the fact that the trend of CC is still in its early stages there are varying and opposing definitions of the phenomenon. As an example the trend currently has four terms to describe it: Collaborative Consumption (CC), The Sharing Economy, The Mesh and The Access Economy. Through this research it was found that CC seems to be the newest and most widely adopted term and is why this term will be 5

applied in the study. Moreover, the main experts on CC that will be used within this study to understand, describe, and analyze the CC phenomenon are Rachel Botsman, Roo Rogers, and Lisa Gansky. Many and varying forms of business models are emerging with this trend, however, for the sake of comparability and specificity this research only focuses on the P2P CC companies in the accommodation industry that offer tourist based options. As such the study does not apply data from sites like Housinganywhere.com, Boligportalen.dk, Findroommate.dk, etc. as these are largely for long-term based rentals and more permanent housing, often with a minimum of 6 months for e.g. student exchanges up to 2-year permanent contracts. In continuation of this, the study only concentrates on hotels, hostels, and CC options for tourists in Denmark mainly due the fact that these have the highest similarities and thus can be compared with the highest amount of validity. Additionally, the availability of data is a reason, as many of the major reports on the subject and Danmarks statistik do not include numbers on bed and breakfast (B&B) establishments and smaller camping sites (Danmarks statistik no. 1, 2014). Furthermore, the data for summer housing and marinas are very dependent on seasonal factors, which could in fact skew the data. This is also seen in the data collected by Danmarks Statistik, which is largely focused on the summer holiday period of May, June, July, August, and September (Danmarks statistik no. 2 and no. 3, 2014).

In contrast, the focus of the study and the elements that guide the analysis are discussed in the following chapter.

CHAPTER 2. THEORIES This chapter offers an overview of the theories and relevant elements that have been selected for the study in order to answer the research questions. For the purpose of studying the phenomenon of CC the chosen three main theories have been combined. To illustrate the flow of the research and the way in which the theories are used together, a theoretical framework has been created linking the three theories.

Figure 3 - Theoretical Framework (Based on Jenkins, Rogers, and Christensen) (Own model, 2014) Â

2.1. The Theory of Convergence Culture As illustrated in the theoretical framework, the study will first look at CC from a broad perspective, using the theory of Convergence Culture to define and make sense of the phenomenon from a theoretical perspective. The concept of convergence culture is defined by Henry Jenkins as the phenomenon â&#x20AC;&#x153;where old media and new media collide, where grassroots and corporate media 7

intersect, where the power of the media producer and the power of the media consumer interact in unpredictable ways” (Jenkins, 2006:2). As such, the flow of content through different platforms and channels enables active participation of consumers, while media producers find themselves in a transition stage requiring them to manage the demand of user participation. In this scenario, the current technologies allow and often enhance the audience’s participation and engagement toward the flow of stories, files, and images that are scattered across multiple platforms (Bailey, 2006:2). Convergence Culture will thus determine the use of technology and popularity traits of the overall CC phenomenon in comparison with the traditional players’ offerings. The theory of Convergence Culture is applied in order to identify the triggers that contributed to media transforming into a broker within the CC trend. The use of technology is one of the main drivers of CC and has as such enabled the phenomenon to spread. Therefore the theory will be used in the analysis to determine how individuals and companies make use of media technologies to create value within the P2P accommodation industry. The intention is to determine what role media plays within CC and how consumer behaviour has changed toward a shared economy where they make use of media to interact with different communities and satisfy their needs. For this, the research will use the three main concepts discussed within Convergence Culture: collective intelligence, participatory culture, and media convergence (Jenkins, 2006). These concepts appropriately describe, from a theoretical point of view, what is really happening within CC and look at what the customers perceive as the main technological value drivers of CC, as they represent the basis on which the cultural shift and consumption behaviour changes take place within the Convergence Culture theory. These are important common grounds that relate both to Jenkins’ theory and to the CC characteristics, as discussed below.

2.1.1. Collective Intelligence The collective intelligence concept has its roots in theorist Pierre Levy’s research on the cultural and cognitive implications of digital technologies. Based on the fact that “no one knows everything, everyone knows something, and all knowledge resides in humanity” (Levy in Jenkins, 2006:26-27). Individuals are now able to, via the Internet, share their own experiences and expertise in the pursuit of meeting shared goals and objectives. Collective intelligence, bringing individuals together, creates what Pierre Levy calls ‘knowledge communities’, which allow people to make use of their aggregated power in negotiations with media producers, but also serving as the “invisible and intangible engine for the circulation and exchange of commodities” (Jenkins, 2006:27). The emerging new forms of communities are specifically characterised by temporary, voluntary, and tactical affiliations, which are constantly affirmed through intellectual endeavours and emotional investments. As a result, Jenkins 8

(2006:27) agrees that these communities are born and survive together as a consequence of the mutual production and reciprocal exchange of knowledge. The glue that holds together these collective intelligence communities is not necessarily the static possession of knowledge, but the dynamic and participatory social process involving acquiring knowledge, as well as continually testing and confirming the group’s social bonds (Jenkins, 2006:54). This social and dynamic process leads to what experts call participatory culture, which is discussed in the next section. The collective intelligence concept within convergence culture thus helps in assessing the ways and reasons for consumers’ behaviour changes toward sharing their knowledge, experiences, and expertise in what authors call ‘knowledge communities’, which is frequently seen among CC consumers. This discussion will enable an understanding of the triggers that drive consumers toward a CC model and what it is that they value most about it, which can be used further in the analysis of diffusion of innovations for the particular case of the CC trend within the accommodation industry.

2.1.2. Participatory Culture Participatory culture represents the second concept involved in the convergence culture discussion and refers to the changes that can be observed with media producers and consumers, as they begin to interact with each other based on a new set of rules (Jenkins, 2006:3). In a participatory culture, Jenkins describes the situation as one where “…consumers are using the new media technologies to engage with old media content, seeing the Internet as a vehicle for collective problem solving, public deliberation, grassroots creativity” (Jenkins in Saxtoft, 2008:21). In other words, the changes that can currently be seen within media are upfront bringing new opportunities and rights for mainstream individuals to contribute to their culture. Consumers are now enabled to take media into their own hands, encouraged by a convergence culture to actively engage and participate. In a participatory culture, convergence enables a cultural paradigm shift in which media companies actively encourage users and fan communities to engage more with the media content and develop emotional attachment. However, in this discussion media companies tend to fear to lose control over the creative and commercial possibilities, while infringement of copyrights can also be a significant problem (Saxtoft, 2008:21). While individuals could initially interact with media content on a computer, and this interaction was relatively easy for media companies to control. In the participatory culture where the Web has become a place for consumer participation including a variety of 9

unauthorized and unanticipated ways to interact with media content, companies need to rethink the way they create and distribute media content. This also refers to the way they allow their users to interact with the media technologies, which is what this study will investigate further. As Jenkins adds, â&#x20AC;&#x153;allowing consumers to interact with media under controlled circumstances is one thing; allowing them to participate in the production and distribution of cultural goods - on their own terms - is something else altogetherâ&#x20AC;? (Jenkins, 2006:133). Having a new set of rules born from the process of convergence, consumers have started to change their mindset and attitudes toward how and why they consume different types of content, leading to a new type of consumer (Table 1).

Old Consumer Type Receiving the content passively

New Consumer Type Highly active and engaging with the media content

Stationary and predictable

Migratory, unpredictable, and declining loyalty toward networks and media content

Isolated individual who receive and treat

More socially connected and enjoys media

content by oneself

content along with many other peers

Compliant

Resistant and nosy toward the content

Table 1 - Differences Between Old and New Consumer Type (Based on Jenkins, 2006:18-19) As a consequence of the shift in consumer types, it is now necessary that media companies rethink the old assumptions about both the ways they share content and how users consume it. Convergence thus reshapes the interactions between companies and consumers in relation to content creation, sharing, and consumption. Moreover, Jenkins (2006) argues that the process of convergence is both a top-down corporate-driven process and bottom-up consumer-driven process. When media companies learn and manage to accelerate the content flow across multiple delivery channels that have the purpose to expand and broaden networks while also reinforcing viewer commitment, they are engaged in a top-down corporate-driven process. But when consumers learn how to use the different media technologies in order to have full control over the media content and also be able to interact with other users, they are engaged in a bottom-up consumer driven process (Jenkins, 2006:18). From this discussion, Jenkins outlines the newness of convergence culture within a participatory culture as

the point where consumers have a desire to take control over the media flow in their lives, participate in their culture, and send their feedback to the media companies (Jenkins, 2006:18). The participatory culture perspective can as such help determine what happens when consumers and companies start interacting with each other, which is the case of CC. The analysis will discuss the trend from this perspective, looking at different media technologies and their role in creating a better communication environment. Understanding the reasons behind using different media technologies for creating and sharing knowledge among users within the accommodation industry will provide insights and arguments for the diffusion of innovation discussion, where the focus is to determine the value attributes that play an important role in the process of diffusion.

2.1.3. Media Convergence Media convergence is the third concept that appears in the discussion related to convergence culture, referring to the new media technologies enabling the same content to reach users on different channels, and under different forms (Jenkins, 2006:11). Jenkins (2006:14) argues that even though a channel’s content can shift, like the storytelling in television took over the radio, the audiences can change, and the social status can shift (e.g. theatre changed from a popular to an elite form), but when a medium satisfies the demand of mainstream consumers, it will continue to function. In other words, old mediums have been forced to coexist with emerging media, and more importantly, old media are not entirely displaced, but their functions and status are changed by the emergence of new technologies. For Jenkins, media convergence “is more than simply a technological shift. Convergence alters the relationships between existing technologies, industries, markets, genres, and audiences. Convergence alters the logic by which media industries operate and by which media consumers process news and entertainment […] convergence refers to a process, not an endpoint” (Jenkins, 2006:15-16). While the original well-known idea of convergence implied that “all devices would converge into one central device that did everything for you”, just like the universal remote, “[…] what we are now seeing is the hardware diverging while the content converges… Your email needs and expectations are different whether you're at home, work, school, commuting, the airport, etc., and these different devices are designed to suit your needs for accessing content depending on where you are - your situated context" (Jenkins, 2006:15). That is to say, media convergence has made it possible for users to access content whenever and wherever they want, showing that while there is a visible pull for more specialized media appliances, this pull now coexists with a push for more generic devices (Jenkins, 2006:15). 11

The media convergence notion can therefore further the understanding of how multiple media technologies coming together has pushed forward the CC trend, and assess the ways in which both consumers and companies can make use of the new media channels enabled by these emerging technologies. This analysis would also lead to further assessment of how and why the CC model is disrupting the traditional accommodation industry, where arguments for the CC networks and media usage are brought into discussion. The convergence culture analysis will bring to the study useful insights as to why consumers are prone to change their behaviour toward a CC consumption model and what values are perceived within this model, providing answers for the research question: “What converging media technologies used in peer-to-peer collaborative consumption are creating perceived customer value and how do they differ from the established accommodation firm’s usage of media technologies?”. These findings will lead the study further into the analysis of diffusion of innovations, where the focus is to better define the attributes that play an important role in the process of CC diffusion.

2.2. The Theory of Diffusion of Innovations Moving a step forward along the theoretical framework, the theory of Diffusion of Innovations provides a model that allows for illustrating both what persuades consumers to adopt to CC and at what rate they are doing so. For this the analysis will use the innovation-decision process, more specifically only the first three stages of this process: knowledge, persuasion, and decision. Figure 4 depicts the parts of the theory that will be utilized, since not all parts of Rogers’ framework are directly relevant for answering the research questions in this study, as they are focused on the continued usage of CC.

Figure 4 - A Model of Stages in the Innovation-Decision Process (Based on Rogers, 1995:163) Before an individual adopts a new innovation (s)he goes through the ‘innovation-decision process’ (Rogers, 1995:20). This is a five-step process through which the individual (or other decision-making unit) makes up his/her/their mind of whether to adopt or reject. (Note that the ‘innovation-decision process’ holds all other aspects of the theory that will be discussed in detail later in this section p. 14). Knowledge relates to when the individual becomes aware of the existence of the innovation and obtains some insights of how it works. The consumer’s focus is in this stage on questions such as: “What is the innovation? How does it work? Why does it work? (Awareness-knowledge), How to use the innovation? What quantity of the innovation to secure? (How-to knowledge) What drives the innovation? What are the functioning principles underlying how the innovation works? (Principles-knowledge)” (Rogers, 1995:165). By identifying the communication channels and social systems that enable the answering of these questions it will become clear how knowledge of CC is gained (Communication Integration – Figure 4). It will also provide insights on the type of communities that utilize CC and the characteristics of the 13

individuals within (Social System Norms – Figure 4), which will lead to a segmentation of CC adopters in the analysis. However, as Rogers points out (1995:167), simply having knowledge of an innovation does not mean that an individual will necessarily adopt, an individual’s attitude toward the innovation also plays a role. This is why the report will also be utilizing the persuasion part of the framework, using the five elements of perceived characteristics (See p. 15), to see what drives people to have either a negative or positive attitude towards CC. The study will largely concentrate on what traits are creating value and persuading consumers to get involved with CC - the positive attitudes that are created. The Decision stage refers to when the individual is in a situation of interaction, which leads to adoption or rejection. This decision of whether to adopt or reject CC will be analysed by looking at how much the phenomenon has grown in the Danish accommodation industry and what types of decision-making mechanisms, such as trials, are being utilized by the CC companies to lower the individuals uncertainty and drive the decision to adopt.

2.2.1. Elements Within the Innovation-Decision Process Everett M. Rogers (1995:11) describes his theory as follows; “diffusion is the process by which (1) an innovation (2) is communicated through certain channels (3) over time (4) among the members of a social system.”

Figure 5 - Illustration of Diffusion of Innovations (Rogers, 1995:11) 14

He further defines the four main elements and their sub-elements as follows: (1) An innovation is defined as being perceived as new by the individual, be it newness in knowledge, persuasion, or decision to adopt. The characteristics of a given innovation are very important as they help provide explanations for the rate of adoption of an innovation, which will vary depending on the relative advantages as perceived by individuals. Rogers has as such outlined five characteristics of an innovation: 1.

Relative advantage (Rogers, 1995:212-223) is about how an individual perceives the benefits of the innovation as better than the previous idea or offering, this factor is the most important, as the rate of adoption will be far more rapid if the innovation is perceived as advantageous. Whether it is perceived advantage in the form of economic profitability, social prestige, savings in time and effort, decrease in discomfort, immediacy of the reward, and other benefits. As such the stressing of the relative advantages of an innovation is an important message to get across to potential adopters as it lowers the uncertainty and thus heightens the willingness to adopt. 2. Compatibility (Rogers, 1995:224-242) “is the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters”. The perceived compatibility of an innovation is thus positively related to its rate of adoption, meaning that if an innovation is incompatible with an individual’s cultural values, norms, needs, and previously adopted ideas the rate of adoption will be slowed. It is therefore important to be aware of the naming, positioning, and presentation of the new innovations so as to make them more compatible with the potential adopters. 3. Complexity (Rogers, 1995:242-243) relates to how difficult the use and understanding of the innovation is perceived to be. The more difficult an innovation is to use the slower the rate of adoption will be, as developing new skills and understandings take time. 4. Trialability (Rogers, 1995:243-244) is concerned with the possibility for individuals to try out the innovation on a limited basis. Innovations that offer trialability will often be adopted faster as the uncertainty for the individual is lowered considerably. Rogers (1995:244) states that the trial offering is most important in the early stages when trying to convince innovators and early adopters, as the later adopters and laggards will look to the former for confirmation. Therefore laggards move from trial to full-scale use at a much higher pace than do the innovators and early adopters, as there is less uncertainty involved due to the already large adoption of the innovation by peers.

5. Observability (Rogers, 1995:244) is related to whether or not others can observe and describe the results of the innovation, the higher the level of observability the more likely individuals are to adopt. By identifying these characteristics of CC it will become clear what it is that consumers value, why the trend is diffusing and thus provide insights for the final phase of the analysis, where Disruptive Innovation theory is applied and suggestions for the traditional players in the accommodation industry are provided. (2) Communication channels are in this case defined as “the means by which messages get from one individual to another” (Rogers, 2003:18). Rogers further explains how ‘mass media channels’ are rapid and efficient channels to use to create awareness-knowledge, through ‘interpersonal channels’, which involve direct contact, are more effective in persuading individuals about an innovation. Thus diffusion is a very social process that often happens through imitation of peers in a network of individuals who are similar in certain attributes like beliefs, education, social status, etc. These communication channels will be identified and discussed in relation to the convergence culture analysis, which as described also deals with what communication channels that are being used to communicate about the new idea. These are one of the clear linkages between the chosen theories and they will therefore overlap here and be combined to identify the media technologies utilized in both the CC and traditional Danish accommodation industry, as well as in the analysis of how users gain knowledge of CC. (3) Time relates to the ‘rate of adoption’, which is the “relative speed with which an innovation is adopted by members of a social system” (Rogers, 2003:22). Ideally, first the innovators and early adopters will embrace the innovation, later more individuals will join and over time only few are left that have not yet adopted. This means that when data on this is plotted onto a graph as seen in figure 5 (See p. 14) it becomes an S-shaped curve, which is typical for innovations. The rate of adoption thus illustrates with what speed an innovation has spread. (4) A Social System is defined by Rogers (2003:23) as “a set of interrelated units that are engaged in joint problem-solving to accomplish a common goal. The members or units of a social system may be individuals, informal groups, organizations, and/or subsystems. The system analyzed in a diffusion study may consist of all the peasant families in a Peruvian village, medical doctors in a hospital, or all

the consumers in the United States”. The sharing of a common goal holds the system together and establishes the boundaries for where the diffusion happens (or is rejected). In some cases, like the Peruvian village case (Rogers, 1995:1-5), the system has higher influence on the rejection or adoption decision of the innovation, than has the individual member’s characteristics. In other words the decision of whether to adopt or reject can happen at both a joint social system level (collective innovation-decisions) or at the level of the individual (optional innovation-decisions) (Rogers, 2003:28). The social system can thus be identified both through “the patterned arrangements of the units within a system” and “the patterned communication flows of the system” (Rogers, 1995:24). Again it is important to point out a clear linkage between the theories, why the identification of the social system (or community) and its patterns of communication and collaboration will be treated in connection with the convergence culture concepts of collective intelligence, participatory culture, and media convergence. In the case of CC it is not the social system that decides whether or not to adopt but the individual who then joins an online social system. Therefore the focus here will be on identifying the patterns and characteristics of the individual that has chosen to adopt CC and thus make up that social system. Consequently using the parts of Rogers' framework, presented above, will enable the study to answer both what converging media technologies in P2P CC are creating perceived customer value and how and why the trend is diffusing among consumers. Furthermore, the rate of adoption is considered to provide findings that can narrow the focus even more, moving forward into discovering if the CC trend has reached mainstream customers and is in fact disrupting the traditional industry, which will be analysed through the Disruptive Innovation theory, as discussed in the next section.

2.3. The Theory of Disruptive Innovation Disruptive innovation is a theory created by Christensen to offer a conceptual method by which to view the cause and effect of products and services. Its purpose is to make it possible for managers to better predict the outcomes when faced with new types of competition from different positions within the market. Christensen’s opinion is that because disruptive strategies are often predicated on competitors increased attention on satisfying their most loyal customers, a customer-focused strategy can result in the downfall of a company (Christensen, 1997:9).

To illustrate, the potential of the CC phenomenon is heavily supported by the disruptive nature of a P2P business model innovation. The P2P platform, together with social media, on and offline communities, and wireless Internet enable the practice of sharing on CC sites, thus facilitating the ability of consumers to interact with each other on a contemporary level. This gives this study the opportunity to explore deeper the underlying entities that stimulate the use of this innovative business model. The Disruptive Innovation theory will therefore also be used to further identify the dimensions of customer value (Christensen, 1997:11) within the CC movement.

2.3.1. Disruptive Innovations Disruptive innovations are innovations that impact the existing flow of business in a particular market or industry. They are a powerful means for extending and developing new markets by interrupting existing segments with new benefits and functionalities created for consumers (Christensen, 1997:12). Disruptive innovations are therefore described as being technically simpler, low-cost, low quality, more accessible and attract less demanding consumers. In order to demonstrate the potential of an innovation to exceed market needs and customer expectations, the relationship between time and performance of a disruptive innovation i.e., its performance trajectory is observed. According to Christensen, the performance trajectory measure is what commonly results in the displacement of market incumbents (Christensen, 1997:11). What Christensen is describing is a transformation within a competitive framework that points to a new measure of customer expectations based on the innovative dimensions of performance over time. Another aspect of this type of innovation is that it will introduce a very different value proposition from the existing paradigm of competitive expectations (Christensen, 1997:11). Consequently, this will often shift customer expectations and competition towards the new dimensions of performance (Bower and Christensen, 1995:45). To further grasp the concept of the theory the study will describe two types of technology driven changes: sustaining and disruptive innovations. However, the discussion will mainly focus on disruptive innovations, as they are more relevant for the study of the CC phenomenon, and displayed in figures 6 and 7 (See p. 19 and 20).

2.3.1.1. Sustaining and Disruptive Innovative Technologies There are fundamental differences between sustaining and disruptive innovative technologies whereby each category is created to explain a relative phenomenon within The Disruptive Theory. Christensen, states that sustaining innovations are about improving the performance of radical or discontinuous technologies, for already established products. Radical innovations are those that have a completely new set of improved performance features at less of the cost, i.e., new benefits (Leifer et al., 2000:5). They are lead product performers that hold value with mainstream consumers. Disruptive innovations are based on performance trajectories and not performance improvements, depending on their potential to disrupt and transform products and services, as illustrated in figure 6. This is because they have a different value proposition that new consumers find useful. In other words, their value proposition allows the disruptive innovations to gain market shares through consumer acceptance. This is what gives them the potential of creating new markets thereby stimulating growth (Christensen, 1997:175).

Figure 6 - The Disruptive Innovation Model (Christensen and Raynor, 2003:33)

To clarify, whilst sustaining technologies stay the course of their current focus, disruptive technologies are believed to change the foundation of competition by changing performance metrics along the lines by which firms compete, thus creating new markets. Christensen further defines new market value as a “unique rank ordering of various innovation attributes in a given market segment” (Christensen, 1997:41). Hence, because of the disruptive potential of innovations to create new markets, a different set of performance measure attributes were needed. Christensen would thus later divide and classify two types of disruptions: new market disruptions and low-end disruptions. It is thereby within this aspect of the Disruptive Innovation theory that helps to describe the build up of CC.

2.3.1.2. New Market and Low-End Disruptions New-market disruptions are defined as disruptions that create new ‘value networks’, while low-end disruptions are characterised as disruptions that attack the least profitable and most over-served customers at the low end of the original value network (Christensen, 1997:11).

Figure 7 - Disruptive Innovation Model: New Market Disruption (Christensen and Raynor, 2003:44)

A new-market disruption takes place when a new product wins over non-consumers, thereby increasing its competitive performance. Non-consumers are consumers that are typically not marketed to, for a product or service. In addition, when a new market disruption occurs, new value networks are created. Christensen defines value networks as â&#x20AC;&#x153;the context within which a firm identifies and responds to customersâ&#x20AC;&#x2122; needs, solves problems, procures input, reacts to competitors, and strives for profitâ&#x20AC;? (Christensen 1997:39). In essence, what Christensen is describing is a business model where a firm creates partnerships with suppliers to respond to the needs of a specific, sometimes untapped, market segment. The premise is that once a foothold is gained the improvement cycle begins and the product is ready for disrupting existing markets. Nonetheless, this type of market disruption becomes a concern for incumbents because they tend to pilfer customers away from their established products or services in existing markets, thus risking the loss of market share (Christensen, 1995:87). The method by which this ensues is what this investigation regarding CC in the accommodation industry is also looking to uncover, i.e, what are the disruptive performance factors and what are they dependent upon. Disruptive Innovation theory is thus used in this study to find out in what ways, if any, the CC accommodation sector is disrupting the traditional industry.

CHAPTER 3. METHODOLOGY This chapter focuses on describing the methods that have been selected in order to research and analyse the case study of the CC phenomenon in Denmark. The sections of the chapter include a discussion about the research approach and design that is used to tackle the phenomenon under study, the data that has been gathered for answering the research questions, the issues related to reliability and validity of the study, and finally the limitations that have been acknowledged by the researchers. The purpose of this chapter is to increase the understanding of the methodological choices that have been made and their application on the case study, according to the methodological framework presented below.

3.1. Research Design Figure 8 illustrates how the basic parts of the methodological framework are connected to the empirical data collected for this report by using a case study of CC marketplaces that are driven by P2P technology. The data derived from literature and other reliable sources allows for the explicit identification of various traits within the CC movement, the investigation of relationships between transference in consumer media consumption, the confluence of media technologies as well as the adoption of CC by mainstream users.

Figure 8 - Methodological Framework (Own model, 2014) The project takes a deductive approach considering three levels of analysis and using theory to guide the process of answering the research questions. Thus the research initially starts in a broad manner focusing on the meso-level of the community, using the theory of Convergence Culture to describe the use of technology and popularity traits of the overall phenomenon in comparison with the traditional playersâ&#x20AC;&#x2122; offerings. Collecting the number and different types of technologies used at each establishment offers insights into what the accommodation providers consider valuable consumer preferences. Therefore, in identifying various characteristics within the CC movement and subsequent knowledge about their media use, the data will provide explicit evidence regarding which media technologies are preferred and offer the best results for consumer engagement. Furthermore, the collected data will also convey how the use of mass media (communication channels) creates awareness and builds interpersonal relationships as these technologies are often embedded in social systems and knowledge communities. These quantitative findings then narrow down the scope of the project, leading to a more qualitative look at what the customers perceive as the main value drivers of CC. Which is the next level of analysis 23

- the micro-level of individuals and their behaviour. Using the theory of Diffusion of Innovations (Rogers, 1995) the study will follow a framework that presents elements of what persuades consumers to adopt into the CC movement and at what rate they are doing so. Here research is conducted on how knowledge is transferred within communities as well as demographics on those who are most likely to be a member of the sharing communities. This allows segments that are likely to adopt CC to be identified while also gathering more details regarding the make-up of the CC social system. The rate of adoption thus brings findings that can again narrow the focus to discovering if the trend is in fact disrupting the traditional industry as described in various online articles (Vision Critical and Crowd Companies, 2014:9 and Altimeter Group, 2013:7). At the macro-level the analysis will study the impact of CC on an industry level in Denmark. In order to determine if a disruption is in progress, data is needed to show by what method it is taking place and what performance measures are needed to assess its trajectory and impact on the industry. Therefore to determine if CC companies are actually disrupting the industry a calculation of the market share distribution in the Danish accommodation industry will need to be determined and compared to the traditional companiesâ&#x20AC;&#x2122; previous shares. As a result, the various findings of value adding attributes and media usage utilised by the CC companies will permit the report to suggest possible technological initiatives for the traditional industry that can allow them to regain market shares. The originality of this study lies in the combination of the three theories and their application on the accommodation industry, rather than the creative industries, which was the case of Jenkinsâ&#x20AC;&#x2122; convergence culture discussions (Jenkins, 2006). This combination of theories and their application on three analytical levels constitutes the uniqueness of this research, where CC is studied and analysed in order to generate more findings about the dynamics within the accommodation industry in Denmark. Moreover, at the industry level, the novelty of the study lies in the approach suggested for the traditional companies, that exclude the typical responses seen in other industries of buying, ignoring, or not considering the new CC companies as a threat. Instead, this study reflects on suggestions that can help traditional accommodation companies in Denmark compete with CC companies, by improving their approach to customers and their services. In addition, this report brings a new approach to studying CC, as during the research it was discovered that there is not yet any study in which the technological media convergence aspect is used as a source for understanding the phenomenon of CC. Even more, it was also determined that in general there is a lack of studies on CCâ&#x20AC;&#x2122;s impact in Denmark.

3.2. Methodological Approach Regarding the approach for this research a case study method will be applied, which is defined as “an empirical enquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident” (Yin, 2009:18). This method is most suitable for this research as it assists in the process of explaining the present circumstances of consumer behaviour changes toward the trend of CC and the facts in relation to attributes of the diffusion of innovations. Just as Yin (2009:4) argues, the case study is relevant for research that has the purpose to answer why and how a social phenomenon works as well as one that allows an in-depth understanding of a phenomenon. When choosing from the variety of case studies that have been mentioned by scholars (e.g. a single organization, a single location, a person, a single event) (Bryman and Bell, 2011: 59-60), this study will focus on the single event option. The research questions applied in the investigation of the CC phenomenon will therefore come from the perspective of studying events that trigger consumption behaviour changes. Bryman and Bell (2011: 61-62) describe three types of case study methods: the revelatory case study that involves research of a case that has not been studied before, the unique and extreme case, and the critical case, which offers a better understanding of the initial study hypothesis. Having these in mind, this study uses the method of a single critical case, with the purpose of testing, challenging, or confirming a well-formulated theoretical framework. In this case, a complex theoretical framework (See Figure 3, p. 7) was created, and as Yin adds, this framework comes “with a clear set of propositions as well as the circumstances within which the proposition are believed to be true” (Yin, 2009:47). Thus, it is argued that the single case can contribute to determining if the theory propositions are correct or if there are alternative explanations that could be more relevant to the investigation of the CC phenomenon.

3.2.1. Exploratory Study The purpose of this research is to define some of the effects that the new phenomenon of CC is having on the accommodation industry. The report will thus conduct an exploratory study using cross sectional data to find out what is currently happening and discover insights in regards to this new phenomenon. The advantage of conducting an exploratory study is that it by definition is adaptable and flexible, allowing for change of direction depending on the explored data. Meaning that the focus of the study is initially broad, becoming increasingly narrower as the research progresses (Saunders et al., 2009:140). This approach is highly appropriate as the trend of CC is only just emerging and there 25

are thus still many unclear definitions of the phenomenon and opposing opinions about what exactly it entails and how it will evolve. Therefore elements of descriptive research will also be utilised in order, as the necessity described by Saunders et al. (2009:140), to “have a clear picture of the phenomena on which you wish to collect data prior to the collection of the data.” In order to answer the earlier defined research questions a mixed method research design was selected for the collection and analysis of the data. The mixed method research combines both qualitative and quantitative data collection techniques (Saunders et al., 2009: 166) and analysis procedures (See further description in Data Collection section below). Using qualitative research techniques provides an understanding of the “subjective and socially constructed meanings expressed about the phenomenon being studied” (Saunders et al., 2009:163), and results in discovering what the perceived customer values are within the CC trend, which are further discussed in relation to the Diffusion of Innovations theory. Applying quantitative research techniques offers the research the possibility to determine the “relationships between variables, which are measured numerically” (Saunders et al., 2009: 162), and results in determining the effects of the CC trend on the accommodation industry in Denmark, which are discussed in connection to Disruptive Innovation theory. Consequently, a mixed method research brings to the study a “richer approach to data collection, analysis, and interpretation” (Saunders et al., 2009:164), while also offering complementarity in the way findings and meanings can be clarified, confirmed, and linked throughout the analysis section. Lastly, a mixed method research offers confidence in the research conclusions because it eliminates the ‘method effect’ by using different research methods to collect the necessary data (Saunders et al., 2009: 169).

3.3. Data Collection The following section describes the data collection techniques used to gather data for answering the research questions. For this, primary and secondary data were collected using document analysis, sampling techniques, and desk research.

3.3.1. Primary data Through document analysis and desk research data was collected, which followed specific variables that needed to be included in order to generate responses for the research questions. Accordingly, the primary data is based namely on numerical data, and includes the following: â&#x2014;? Email correspondence: gave numerical data on growth, listings, and members for Airbnb, specifically for the Danish market. â&#x2014;? Websites and articles: were reviewed to gather numerical data specific to the accommodation industry in Denmark, which provided the opportunity for a comparison of the differences between the CC companies and traditional accommodation businesses in terms of identifying the players within the Danish industry, their technological application, pricing, and growth. Using a variety of reputable websites and documents generated data for mapping the selected accommodation players in Denmark. The comparing variables consist of the number of companies, their listing, and related capacity specifications. The technological application was investigated through desk research, comparing the usage of media technologies in accordance with the relevant elements dictated by the Convergence Culture theory and the identified media usage of Danes (See p. 30). Here it was a necessity to apply a sampling method to narrow down the amount of hotels and hostels to examine, as described in more detail in the next section. In the case of determining the pricing of the different players, cost savings data was collected. This was done through collection of quantitative data in the form of low prices of rental properties from the websites of the selected accommodation providers. The data was further used in the analysis in accordance with the Diffusion of Innovations theory, where findings demonstrate that cost is an important factor triggering the adoption to CC and therefore important to discuss. Research of the differences in growth involved analysing numerical data on the amount of rooms (or listings) available at hotels, hostels, and CC companies, the amount of stays for these accommodation types, the number of new CC entrants in Denmark, the rise in amount of members, and the distribution of market shares. This data was used in the analysis to determine the rate of adoption and overall diffusion of the phenomenon in Denmark as well as the level of disruption caused to the traditional players in the industry. 27

3.3.1.1. Sampling Frame and Stratification In order to have equilibrium in the data collected for the different components of the research (hotels, hostels and CC companies), a probability sampling method was used to better define the focus for the data collection. The purpose of using probability-sampling methods is to generate various types of statistical information of a qualitative or quantitative nature by only examining selected elements from an entire population study (Saunders et al., 2012:262). Part of the investigation in this study is to determine how the accommodation sector in Denmark utilises media technology. Therefore by defining the types and methods by which media technologies are used and drawing comparison between the sectors, will offer some insights into why the CC accommodations are slowly gaining more traction in the market. The sampling method would also be a way to narrow down the number of units to study, especially when looking at what media technologies the units are using, as illustrated in figure 9. For this purpose, the data collected is from companies in the accommodation industry located throughout Denmark. A list assembled from the accommodation industry includes hotels, hostels, as well as the non-traditional Internet based P2P CC accommodations operating in Denmark: Airbnb, HomeExchange, Roomorama, Couchsurfing, Vacation Rental By Owner (VRBO), 9Flats, Wimdu, HouseTrip, HomeAway and FlatClub.

Figure 9 - Stratified Sampling of the Accommodation Industry in Denmark (Own model, 2014) Using a sample frame enabled the collection of similar members from a larger sample pool that represents the entire accommodation industry in Denmark (Saunders et.al, 2012:262). Furthermore, because the data collected also comprises of hotels in different categories (luxury, low-cost, boutique, etc.) a stratified sampling method is needed. Equally important is the fact that by stratifying the industry in the sample frame further allows the accommodation sector to be divided into three subgroups of strata, namely hotels, hostels, and CC accommodations. The method by which this was carried out was to use the sampling frame to narrow the sample pool of the hotels and hostels using the process of stratification of selected attributes to further categorise the data. The attributes included the most popular hotels and hostels, the number of most rooms (biggest) the number of least rooms (smallest); the most expensive and low-cost as well as the location: city centre or country side.

Other variables included were the largest hotel chains (number of most hotels in Denmark) as well as smaller independent hotels and hostels. Therefore by sampling within the stratum offers each sample an equal chance of representation. The sampling methods helped the study focus precisely on the selected accommodation providers, as well as restrict the focus to specific relevant variables for further analysis, namely the identification of media technology usage.

3.3.1.2. Justification of Converging Media Technology Research Choices According to a report on the Danesâ&#x20AC;&#x2122; IT usage from Danmarks Statistik (no. 4, 2013) where 5,696 respondents between the age of 16 and 89 participated, 56% use the Internet (websites) to seek or purchase travel or overnight stays, the amount is equal for both men and women. Having a website that is responsive, meaning that it is also accessible from mobile or tablet is of great importance as 59% use their mobile to access and conduct searches on the internet. Applications (Apps) should also be considered as 50% use these frequently, additionally it is important to be aware of the versions the app is offered in as the available smartphones and thus operating systems are many and varied in Denmark (Kielstrup, 2012). Therefore these elements have been deemed as a necessary part of the analysis on media technology application. The choice of social media sites in this study is based on their popularity and usage in Denmark according to YouGov Denmark (2013), who interviewed 2,061 Danes between the ages of 15 and 74 about their attitudes towards and use of social media. Furthermore, the chosen sites are ones that allow for convergence culture and CC principles of sharing and creating own content that could be linked to any given travel experience (highlighted in blue in Table 2), thus omitting unrelated popular sites like Netflix (Video-on-demand), Spotify (Digital music service), LinkedIn (Business oriented online network), etc.

Table 2 - Knowledge and Usage of Social Media Sites in Denmark (YouGov Denmark, 2013:9) Lastly, desk research was conducted in order to identify if any users have generated online content, fan sites, and communities or physical memorabilia as defined and discussed by the concepts of collective intelligence and participatory culture in the Convergence Culture theory. In connection with this the availability of the companiesâ&#x20AC;&#x2122; on-site ratings, forums, fan sites, and communities have also been investigated. This media technology research generated data useful for the analysis based on Convergence Culture theory, where such findings provided a background understanding of the CC phenomenon and more precisely indicated consumer behavior and usage of media technologies.

3.3.2. Secondary data The types of secondary data used in this study were collected using desk research. When researching the general phenomenon of CC, mostly US articles, literature reviews, and industry studies were used; as such articles and studies are not readily available for Denmark. However, specifics on the accommodation industry and consumer behaviour are researched using articles, books, and studies 31

that are more related to Denmark. Consequently, the secondary data is based on documentary data, and includes the following: ● Books: were used for theoretical guidance, providing frameworks to follow throughout the study. Additionally some acted as a lexicon for describing and defining the trend of CC, offering important insights for how the trend is changing consumer behaviour, the triggers of the trend adoption, and the impacts on the industry. ● Articles (literature reviews, journals, and news): offered suggestions on the theoretical application of the theories along with critical points to be aware of and in some cases further define or avoid. Moreover, they provided additional information and perspectives on the CC trend. ● Publications (industry studies): provided insights on the accommodation industry’s specific focal points, data, and technology application. ● Websites: gave background information and insights into how the trend was evolving and disrupting. ● Videos: offered insights on what users value about the trend and their usage of media to share their experiences, but also details about the different accommodation offerings. ● Presentations: provided background information about the CC trend and relevant data for the current economy.

3.4. Reliability and Validity To ensure an accurate representation of the quantitative and qualitative data collected for this study the concepts of reliability and validity will be used. Reliability refers to whether or not the study data collection techniques and systematic procedures could reproduce consistent findings by other researchers, i.e., can the results be replicated (Saunders et al., 2012:192). In this case, if another research would follow the same research design involving the same research strategies and a data collection based on the specified variables, the replication of the study would be possible. However, the results may not be replicated at another point in time due to the fact that the numbers in the accommodation industry and in particular in the case of CC offerings are growing at a fast pace, as it was observed when collecting data. The quality of the study research using only the concept of reliability is ineffective. Therefore validity is needed to help strengthen the quality of the research. Validity determines whether the research truly measures that which it was intended to measure (Saunders et al., 2012:193). For this, it was ensured 32

that the data collected through the use of reliable sources, sampling techniques, etc. corresponds to the elements dictated by the theory and thus answers the research questions in a valid manner. Equally important is the use of triangulation. Triangulation is defined as "a validity procedure where researchers search for convergence among multiple and different sources of information to form themes or categories in a study" (Creswell et al., 2000:16). This study uses triangulation when gathering the data. For example, when creating the accommodation providers sampling or gathering accommodation capacity numbers, multiple sources have been used in order to verify the findings and assess their credibility. To further ensure the reliability and trustworthiness of the data collected, the study considered using reputable known sources for gathering primary data. Thus, the methodological considerations accompanied for this study are represented by data collected from the following sources: Danmarks Statistik, VisitDenmark, YouGov, and HORESTA. Furthermore, all data, that was not found from an industry specific source, were cross-referenced by verifying the data from at least two sources in order to heighten the sample validity and accurately reflect the overall industry. Concerning generalizability, the overall findings of the study in terms of consumer behaviour, characteristics, and perceived values can be generalized for countries where CC is entering the market. However, concerning the trend's diffusion and its disruptive effects, the findings cannot be generalized as they are based on data specific to Denmark. Similarly, legislative impacts, which can affect the spread and effect of the phenomenon, could vary across different countries. Given these points, using all three concepts, reliability, validity, and triangulation is important in ensuring the quality of the research and that there are no ambiguities between the data and the study research questions.

3.5. Limitations When conducting a cross-sectional study it is important to note that it does not provide a full picture of the relationships of the characteristics of an innovation and the rate of adoption. Rogers (2009:213) highlights this fact through the example of the VCR which in 1980 cost $1,200 compared to $200 in 1993, meaning that the relative advantage of the innovation increased tremendously in regards to economic profitability. Thus when studying an innovation cross-sectionally it is important to acknowledge the fact that the innovation evolves and the defined relative advantages at one point in time may not be the same at another point in time.

The report has met some constraints when collecting data for hostels in Denmark. That is to say, one constraint comes from the fact that Danmarks statistik includes only the data for hostels that are part of the Danhostel group (Danmarks statistik no. 5, 2014). This situation has lead to investigating the amount of rooms in hostels from less official sources, such as touristonline.dk. Regarding the research on CC, it is important to mention that the constraint of not knowing the exact correct number of hosts and members within the CC platforms is acknowledged in this study. The amount of available P2P rented rooms or subscribers cannot be completely accurate due to the fact that some users can be present on many or even all CC accommodation websites in Denmark, renting their places or searching for places to stay. This represents a constraint for the study as the CC companies do not publicly provide accurate data about their users, being almost impossible to track users as their usernames can vary from platform to platform. This also relates to why the data in the study is built on number of hosts and listings, as there is close to no available data on the amount of renters who browse the sites and as such no comparison of the hosts vs. renters. Additionally it is important to note that due to the fact that the CC companies are in growth in Denmark the numbers identified at the time of writing this report will no longer be accurate when the study is finished. As an example Couchsurfing has had 200 new members, VRBO 87 new members, and HomeAway 95 new sign-ups in a month. As a consequence of accommodation offers changing over short periods of time and inaccurate numbers for such variables collected in this study, the research approached CC companies requesting through direct contact via email any numbers that they can provide for number of listings, growth in number of members, etc. A response with such details from Airbnb Communication Specialist Anne Sofie Kirkegaard (2014) was received (See Appendix I, p. 93) This was, however, the only response obtained, which consequently meant that the data had to be estimated based on Danish news sources such as Finans, Politiken, Jyllands-Posten, etc. In the process of gathering data in connection to listings and overnight says for CC accommodation companies, the study has met the limitation of not getting any information that can contribute to the overnight stays calculations for some of CC players. As one user on HomeAway-VRBO community forum replies, "I asked the same question to someone at VRBO and was told they do not give out that information for privacy reasons. I pointed out that other sites provide you with that information and they said it just isn't their policy (...)" (HomeAway, 2013). The same applies for CC company Wimdu, who has not yet provided any numbers about the booked guest nights (Wauters, 2012). To tackle this

issue, the study has made an estimation based on the available data from HomeExchange. The data available from Airbnb was seen as an extreme case due to its rapid growth rate, which could not be applied to all the CC companies providing accommodation in Denmark. Therefore, HomeExchange numbers have been applied as a guideline for the correspondence between listings and overnight stays for the remaining CC companies as these represented a more appropriate case scenario (See Appendix II, p. 94).

CHAPTER 4. ANALYSIS This chapter presents the findings of the study that is guided by the main research question: What is the perceived value of peer-to-peer collaborative consumption from the consumersâ&#x20AC;&#x2122; perspective and how can traditional players in the Danish accommodation industry take advantage of it and regain market share? The discussions within this chapter will be in the context of the analytical framework (See Figure 10, p. 37) where an understanding of the phenomenon of CC is gained through the analysis of qualitative and quantitative data, collected from primary and secondary sources presented in the methodology chapter. Each sub-chapter is structured around two secondary questions that initially guide the analytical process: 1. What converging media technologies used in peer-to-peer collaborative consumption are creating perceived customer value and how do they differ from the established accommodation firmsâ&#x20AC;&#x2122; usage of media technologies? 2. How and why is the trend of peer-to-peer collaborative consumption diffusing among consumers disrupting the traditional business players in the Danish accommodation industry? The purpose of this chapter is to describe the analysis using three different levels: micro, meso and macro. This process follows the traditional convention of studying the analytical levels for research, however, for this study, and in order to provide a strong background for the reader assessing the CC phenomenon; the analytical presentation for this study, will be as follows: meso, micro and lastly macro.

Figure 10 - Analytical Framework (Own model, 2014) First the order of analysis will discuss the meso-level where the focus is on understanding and defining CC through convergence culture. This is a broad discussion of CC, which is considered necessary for the reader to have a deep understanding of the CC trend within the accommodation industry before going into a detailed discussion about the use of media technologies by the providers of accommodation in Denmark. Next, the analysis that has already identified the CC communities and their characteristics will discuss the micro-level, narrowing the focus to individuals that adopted the trend and the speed of adoption. This discussion is based on the Diffusion of Innovations theory and leads to important data as to why and how individuals adopt the innovation based on the attributes that they value most about it. Finally, the analysis will discuss the macro-level looking at the industry and the consequences that the alternative accommodation has brought to the traditional accommodation industry, based on the findings revealed by both the meso and micro levels. The reasons for choosing this order of the levels of analysis are that the study needs first to get the data from the meso-level (online communities characteristics, participatory culture features, media technology usage), and combine it to the data generated at the micro-level (social system and adopters' characteristics, perceived attributes of CC accommodation and its adoption rate), in order to discuss the macro-level of the 37

consequences of CC for the accommodation industry in Denmark. At this level, all the findings generated before contribute to understanding the market disruption and offer ideas for suggestions that the traditional accommodation companies can apply to regain some of the market.

4.1. Convergence Culture Analysis of Collaborative Consumption There is visible proof documented by many experts (Botsman and Rogers, 2011, Algar, 2007) that individualsâ&#x20AC;&#x2122; consumption behaviour is starting to change from what is called hyper-consumption toward new ways to create value from shared resources, for the greater good of the community (i.e. CC). While hyper-consumption was a cultural phenomenon based on excessive consumption of goods influenced by the globalization dynamics (Abrahamsen, 2013). Rachel Botsman defines CC as â&#x20AC;&#x153;an economic model based on sharing, swapping, trading, or renting products and services, enabling access over ownership. It is reinventing not just what we consume but how we consumeâ&#x20AC;? (Botsman, 2013). The trend of CC is relatively new and is defined by Lisa Gansky as a model where consumers have more information, tools, choices, and power, while businesses have understood and exploited "the perfect storm of mobile, location-based capabilities, Web and social network growth, changing consumer attitudes, and the historically understood benefits of shared platforms" (Gansky, 2010:5). Therefore, the reasons the CC trend has taken so much momentum from a business perspective are represented by the rapid growth of mobile and social networks, which allowed customers to access products and services in a more efficiently and personalised manner (Gansky, 2010:28). Additionally other global factors have also driven the trend forward and triggered significant changes within consumption behaviour. These include the economic crisis that brought distrust in older brands, a willingness toward trying new brands, and individuals rethinking their purchases choosing products that brought more value at less cost. In addition, the climate change and food security issues act as triggers for the trend, where efficient resource sharing triumphs against buying more and owning more. Lastly, population growth and greater urban density has enabled the trend to speed up (Gansky, 2010:28-29). CC includes a variety of activities, such as clothes swapping, tool exchanges, toy sharing, couchsurfing, crowdfunding, P2P rental, ridesharing, and many other activities alike. To better understand how they work, Botsman and Rogers (2011) classify these activities into three CC systems: Product Service System, Redistribution Markets, and Collaborative Lifestyles.

Figure 11 - Collaborative Consumption Systems (Botsman and Rogers, 2011:95,121,151) These systems result in countless relationships and social connectivity, where Botsman and Rogers (2011) consider the trust within P2P interaction as the most important factor of the exchange. In this context, the report will focus on the Collaborative Lifestyles system, more precisely on the P2P accommodation industry within the travel sector, investigating from a media converging perspective how collaborative lifestyles take ideas grounded in old values - openness, community, accessibility, and collaboration - and reinvent them into a modern paradigm. In order to have an understanding of what is currently happening within the accommodation industry in Denmark, the following paragraph defines and further explains the characteristics of the identified main actors in the accommodation industry, both traditional and P2P CC companies, in relation to their numbers and capacity in Denmark. There are currently 958 Hotels in Denmark with a room capacity of 54,833 (HORESTA no. 1, 2011). The hostels have around 3,531 rooms (See Appendix III, p. 95) spread over approximately 114 hostels in Denmark, where 95 belong to the Danhostel chain (Vandrerhjem i Danmark, 2014), which is a voluntary association entirely funded by the membership fees from the chainâ&#x20AC;&#x2122;s many hostels (Danhostel, 2014). Additionally it is important to mention that in order to stay at a Danhostel in Denmark or any other hostel that is a member of Hostelling International (HiHostels) one must either 39

have a hostel membership card, which costs 70 DKK for Danes and 160 DKK for other tourists, or pay an extra fee of 35 DKK per night (Danhostel Randers, 2014). As for the CC companies, currently there are 10 P2P accommodation sites with availability in Denmark:

Figure 12 - Collaborative Consumption Companies - Available Listings in Denmark (Own model, 2014) Together these sites have approximately 80,005 rooms, apartments, houses, etc. available in Denmark, with Couchsurfing being the largest, having 44,711 hosts and FlatClub being the smallest with only two available apartments in Denmark (See Appendix IV, p. 97). The players in the Danish accommodation industry and their capacity is thus distributed as reflected in the image below.

Figure 13 - Defining the Main Actors in the Danish Accommodation Industry (Own model, 2014) 40

4.1.1. Collaborative Consumption Explained Through Convergence Culture Theory In order to understand and determine the use of technology and popularity traits of the overall CC phenomenon in comparison with the traditional accommodation players’ offerings in Denmark, the next section will focus on making sense of the CC phenomenon by looking at it through convergence culture lenses. In doing so, the analysis will explain the CC model by using the three concepts discussed within convergence culture: collective intelligence, participatory culture, and media convergence, in the pursuit to understand, from a theoretical point of view, what is really happening within CC and look at what the customers perceive as the main technological value drivers of CC. When looking at any type of transaction, Botsman and Rogers (2011) mention the economic concept of ‘coincidence of wants’, which refers to the fact that when two individuals are exchanging goods, each side must want the good the other is offering. While this situation rarely happens under normal circumstances, CC has overcome this barrier through the Internet. The CC sites enable diverse and dispersed individuals to connect on a global scale, with the purpose to match their haves and wants with others they have never met. Experts say technology plays a major role in this situation by enabling a sort of trust between strangers, which fuels the "cyber bartering community" to grow at unexpected rates (Botsman and Rogers, 2011:158). This in fact is how Henry Jenkins (2006:2) describes convergence culture; the cultural shift that encourages consumers to search for new information and make new connections within the scattered media content. The shift in the core values of the consumer mind-set has enabled the growth of CC, where experts say individuals are now seeking simplicity in the way they live as a traditional community with strong ties, transparency, and traceability of the products and services they consume, and active participation with more control over their lives (Botsman and Rogers, 2011:51). These characteristics of CC are very closely related to the concepts underlying Convergence Culture theory, more precisely collective intelligence and participatory culture.

4.1.1.1. Collective Intelligence Starting from Pierre Levy’s assumption that “no one knows everything, everyone knows something, all knowledge resides in humanity” (Levy in Jenkins, 2006:26-27), in a CC model users are enabled on the CC platforms to express their reviews and personal experiences about renting different places. Technology advancement enabled individuals to engage not only in product and service bartering, but also in information sharing across multiple platforms. Beyond the accommodation sharing platforms,

the P2P CC phenomenon has enabled individuals to return to the old traditional community, where trust and relationships were easily created. However, in a CC model, the trust between peers coming together in a relationship of exchanging goods has been created by the use of technology, through reviews and rating systems implemented on CC rental sites. Botsman and Rogers argue that these “online reputation systems are a new mechanism for trust between individuals anywhere in the world, and could become a cornerstone for the modern economy” (Botsman and Rogers, 2011:219). Moreover, they create a sort of reputational capital, which claims ‘you can trust me’ and acts as a secondary currency. Being able to access the ratings and reviews about a host renting an accommodation place is an essential part of P2P CC, and this can be explained by Pierre Levy’s concept of collective intelligence, which Jenkins applies in his theory. The fact that people engage in information and knowledge sharing across CC platforms relates to the way Levy describes collective intelligence, “referring to this ability of virtual communities to leverage the combined expertise of their members. What we cannot know or do on our own, we may now be able to do it collectively” (Levy in Jenkins, 2006:27). Collective intelligence forms what Jenkins describes as knowledge communities, the “invisible and intangible engine for the circulation and exchange of commodities” (Jenkins, 2006:27), which in the case of CC refers to the on-site communities and the groups of individuals gathered around the different CC accommodation sites. Jenkins argues that knowledge communities within convergence culture are voluntary, temporary, and based on tactical affiliations (Jenkins, 2006:57). In the case of CC, knowledge communities are voluntary, where peers get involved in such communities because they need to satisfy a specific need, they need some sort of information or they want to share their knowledge and experience about a specific place they rented. These communities form on the basis of tactical affiliation as members intentionally seek to get involved and want to meet their emotional and intellectual needs in finding the perfect place to rent for their travels. However, these communities are not temporary because even if some users leave the community when their needs have been satisfied, they get replaced by others who engage in the community, seeking to satisfy a specific need or sharing their knowledge about a specific accommodation space. This way, the task or mission of the community never ends. Therefore, as Jenkins (2006:27) agrees that these knowledge communities are born and survive together as a consequence of the mutual production and reciprocal exchange of knowledge, the same happens in the case of CC communities. In this context, CC companies have learned to invest in these communities and encourage a multi-way conversation, where the focus is “less about the top-down approach and more about establishing

communities, entwining the reputation of the user and the organizationâ&#x20AC;? (Botsman and Rogers, 2011:204). This can be explained though Convergence Culture theory, where convergence reshapes the interactions between companies and consumers in relation to content creation, sharing, and consumption. The top-down corporate-driven process, when media companies learn and manage to accelerate the content flow across multiple delivery channels that have the purpose to expand and broaden networks while also reinforcing viewer commitment, it is still present but in decline in CC. However, the situation when consumers learn how to use the different media technologies in order to have full control over the media content and also be able to interact with other users, describes the bottom-up consumer driven process (Jenkins, 2006:18), which is more and more visible within CC. Jenkins adds an important note, also applicable to the CC phenomenon, saying that the newness at this point is outlined by consumers strong will to take control over the media flow in their lives, participate in their culture, and send their feedback to the media companies (Jenkins, 2006:18), just as it happens to users offering their feedback and reviews to CC accommodation places. What holds CC communities together is the trust, but also the social process of sharing and getting useful information throughout personal reviews. This is explained through convergence culture by the assumption that every member of the community has some information to put on the table. Every CC user is able to enrich the collective intelligence with their knowledge and experiences, in order to reach a collective goal, which is getting all the information about different rental places, and finally finding the perfect place to rent for their travel. In addition, shared real-life experiences about the places that individuals rented are more highly valued in a collective intelligence community, rather than information coming from a hierarchical system (Jenkins, 2006:54). The CC trend has enabled individuals to seek for freedom of expression in association to the brands they choose, and experts mention that CC companies actively encourage users to make their own videos of the places they have rented, while providing the necessary platforms for guidance, ideas, and complaints. As a matter of fact, some of the most popular CC accommodation companies (e.g. Airbnb, Couchsurfing, Roomorama, and Homeaway) provide either a forum or a how-to guide for using their platform and creating valuable content that would attract potential renters and hosts (See Appendix V, p. 99). In other words, P2P communities function based on their constant sharing of personal experiences, which other peers value and trust, in contrast to any advertisement or promotional messages. Just as Jenkins argues with convergence culture, these collective intelligence communities survive based not on the static possession of knowledge, but on the dynamic and participatory social process involving acquiring knowledge, as well as continually testing and confirming the groupâ&#x20AC;&#x2122;s social bonds (Jenkins, 2006:54). 43

4.1.1.2. Participatory Culture The CC phenomenon can be discussed from the perspective of a participatory culture that is seen within convergence culture. In a participatory culture, Jenkins describes the situation as one where consumers actively engage with online content through new media technologies (Jenkins in Saxtoft, 2008:21). Starting from his definition, it can be argued that this describes what is happening within CC, where consumers start to change their mindset from what was called hyper-consumption to a CC model. Hyper-consumption relates to trying to sell anything by turning consumer wants into everyday habits (Botsman and Rogers, 2011:21-22). Accordingly, in a participatory culture changes can be observed with both media producers and consumers, as they begin to interact with each other based on a new set of rules (Jenkins, 2006:3). In this context, Botsman and Rogers argue “people cooperate not because of friendship or trust in each other, but the trust in a promise of keeping a durable relationship that could benefit them in the future” (Botsman and Rogers, 2011:143). Moreover, Botsman and Rogers (2011) argue that CC meets the same consumer needs, as did the old consumption model, but it brings forward more opportunities than the old one. As a consequence, consumer behaviour and consumption behaviour in general started to change, revealing a new profile of the CC consumer. Individuals are relearning how to create value and use available resources in ways that foster a balance between self-interest and the good of the community. CC experts add to this that individuals can now participate in CC but still keep their "autonomy and individual identity" (Botsman and Rogers, 2011:69-70). The model of CC implies that individuals can participate, they can either be peer renters, sharing their assets with their peers, or they can be peer users, consuming the available products and services. Some choose to be both, but experts argue that while some are “forward thinking and socially minded optimists, (…) others are individuals motivated by a practical urgency to find a new and better way of doing things” (e.g. access a better service like renting a low cost accommodation, allowing closer relationships with people rather than brands, etc.) (Botsman and Rogers, 2011:70). These citizens seek a world where “each individual could act in his or her self-interest and at the same time produce a unified social sphere, in which we’re ‘all one’” (Botsman and Rogers, 2011:71). Looking at the CC consumer profile as described by the CC experts, it can be correlated to the way Saxtoft (2008:21) described users in a participatory culture as becoming more active and seeking participation in relation to media content. Within a participatory culture, users start to engage with the media content and some of them even start generating new content. This can be seen within CC companies, as they have understood the opportunities from having user-generated content and some of them (e.g. Airbnb, HomeExchange, 44

9Flats, FlatClub) have created the necessary conditions for users to share their feedback and experiences (Jenkins, 2006:160-161). Moreover, users actively participate in communities with their own videos and reviews, and there are numerous videos on YouTube from individuals who rent out places and want to show potential renters the overview of the accommodation, but also individuals who have experienced a holiday in one of the accommodation spaces from CC websites. These videos include either the host’s presentation of the house, or the tenant’s personal feedback and other recommendations. This brings important knowledge to the CC community, and Botsman and Rogers say that “community is in the DNA of collaborative consumption (…) consumers are embraced as members and not as users (…) given all traditional benefits for joining a club: status, identity, shared interests, and ownership” (Botman and Rogers, 2011:204).

4.1.1.3. Media Convergence Media convergence, according to Jenkins is an ongoing process that should not be viewed as a displacement of old media but rather as an interaction between different media forms and platforms (Jenkins, 2006:282). In the analysis, one aspect of Jenkins’ theory of Convergence Culture is how the phenomenon introduces new ways in understanding the cultural shift of media consumption. In other words media is thought of as ‘situated context’ in the perception that its context of use is dependent on whatever a user is doing at the moment as well as how they derive value from what they are presently doing. The analysis also reflects how changes in consumer media preferences are related to the changes in their media needs, with each new adoption of media. Jenkins describes this behavior as a new consumer type whereby the active consumption of media gives them more power to compile their own content. Meaning, because of the participatory nature of media technologies consumers are now actively involved in creating their own production and distribution of media, often via social media sites. In order to make an assessment of how traditional hotels and CC accommodation companies are using media technologies a brief contrasting analysis of each selected media is discussed (See Appendix V and VI, p. 99 - 103).

Table 3 - Media technologies: analysis of traditional hotels and hostels (Own model, 2014)

Table 4 - Media Technologies: Analysis of CC Accommodation Providers (Own model, 2014) 46

(1) Responsive Design Responsive design is a web design that can be viewed properly regardless if a customer is using a desktop, laptop, mobile, or tablet device. The data shows that 71% of traditional hotels and 83% of hostels are using responsive design in comparison to 100% of the CC companies. The use of responsive design is important for both the traditional sector and CC, however the findings suggest that CC are more effective at using this design tool in providing a flexible, seamless user viewing experience, especially when considering that CC uses a P2P online marketplace for (online) bookings that is accessible across all smart devices. (2) Applications (Apps) An application is typically used as an extension of a website that can be deployed on multiple digital devices. It is a distinct software program that runs internally within the operating system (OS). The analysis includes only Apple’s iOS and Google’s Android app versions, as they are the most popular and frequently used in Denmark(Ladingkær, 2014). This analysis of app usage covers three areas: (a) have an app, (b) which OS system is used and (c) compatibility with tablets. Only 28% of hotels and 17% of hostels have an app and with 14% of the apps using both iOS and Android OS and also being compatible with tablets. In comparison with CC companies, 50% have an app; both iOS and Android OS systems are used and are compatible with tablets. The findings thus show that CC companies are better at offering all around accessibility to their sites by distributing media across multiple platforms effectively. (3) Social Media The social media channels selected for this study include: Facebook, Twitter, Instagram, Google+, YouTube and Pinterest. They are grouped together because they all share commonalities of convergence culture in encouraging the build up of collective intelligence, knowledge communities, and participatory culture via media. That is, consumers take control of their media usage by “reworking its content to see their personal and collective interests” (Jenkins, 2008). According to the findings, CC companies often use social media as a form of identity authentication in order to build trust between strangers (Botsman and Rogers, 2011:91). The analysis also reveals that CC companies are better equipped to exploit the immense reach and benefits of social media channels as well as how to interact with consumers than the traditional accommodation sector. They have demonstrated how online communities are built not only with social media but also across multiple media platforms (See Table 5).

Table 5 - Media Technologies: Social Media Connections (Own model, 2014) (4) On-site Rating System: Comments and Reviews Rating systems are considered a way to build trust among strangers as hotels, hostels, and CC companies rely on them to provide reciprocal reviews and comments. On-site rating system is a form of networking in what Jenkins considers collective intelligence that in turn creates â&#x20AC;&#x2DC;knowledge communitiesâ&#x20AC;&#x2122;, that allows people to aggregate their reviews. Furthermore, because knowledge communities require one to interact with each other and participate in the dialogue, a by-product of this is that of participatory cultures and a sense of community. However, most hotels and hostels are often vicariously linked or self-linked to third party sites like TripAdvisor whereas CC providers have built in on-site rating systems. The analysis shows that 71% of hotels and 33% of hostels are linked to TripAdvisor in comparison 80% of CC companies have their own ratings systems. Yet 20% of CC companies are also linked to TripAdvisor. Moreover, the findings indicate that users of CC companies are sharing massive amounts of detailed information about their adventures, often low-cost, experiences directly on the CC sites. While users on TripAdvisor comments are usually more business or administrative focused, e.g., customer service and mostly used as a negative outlet for consumers. CC companies thus, have a greater advantage over traditional companies by having a built in on-site ratings system as it presents a more authentic display of their commitment to users, as well as direct access to relevant data.

(5) On-site Communities: Forums and Fan Sites On-site communities including forums and fan sites are often an effective way for traditional and CC companies to interact with users of their services, as both a follow up and feedback response. However, only 14% of hotels and 17% of hostels have on-site communities compared to 40% of CC companies. Neither hotels nor hostels have any forums or fan sites in comparison to the CC companies where 30% of them have forums and 20% have fans sites. Nonetheless, the findings thus imply that CC companies are using the idea of participatory culture by which to continue customer engagement through fan communities long after the users needs with the service were satisfied. (6) User-generated Content To show how users are interacting with hotels, hostels, and CC companies, this study also looked into user-generated content: (a) User-generated YouTube channel, (b) User-generated memorabilia. Hotels and hostels have no user-generated YouTube channels, although there are several ‘marketing’ videos by other travel agencies. While CC companies’ user-generated content are still only at 10%, they are though working to find new ways to engage consumers. An example is Airbnb’s attempt to create a ‘user-generated’ movement by letting its users customise their own Airbnb symbol via its ‘create’ website. Furthermore, user-generated content is part of the participatory culture and has the potential to spread across different media. Therefore the method by which Airbnb are connecting with their users via the create website is a great way to build online communities and advocates for their brand.

Figure 14 - Airbnb’s Create Campaign (Airbnb no.2, 2014) 49

What the analysis of the data and research shows is that the drivers that attract people to use CC companies over traditional ones are rooted in trust, a sense of belonging to a community, flexibility, variety, economic value, fun, and authenticity. The media technologies selected for this study and subsequent data demonstrates this connection more within CC companies in comparison to the traditional hotels and hostels. The findings also show that CC companies are better at utilising media technologies than traditional hotels and hostels although, they are supplemented by the disruptive technology of P2P marketplaces and the underlying principles based in convergence culture, namely knowledge communities, collective intelligence, and participatory culture. Meaning, that CC is embedded in technologies and behaviors of online social networks by the posting of comments, sharing files, code, photos, videos, and knowledge (Botsman and Rogers, 2011:xx). Whereas convergence culture is a process that fuels technological shift in patterns of media ownership by highlighting how consumers are involved in the way media is produced and consumed (Jenkins, 2004:16). In essence the process of convergence culture strengthens the phenomenon of CC and thus offers an advantage to CC companies in the accommodation industry operating in Denmark. By differentiating the methods by which hotels and hostels are using media technology versus CC companies the analysis illustrates how media convergence is reshaping the landscape within the accommodation industry in Denmark and where the key to understanding customer relationships is to understand their consumption of media and allow them to take part in designing this consumption.

4.1.2. Convergence Culture Analysis Takeaways Convergence Culture Theory: â&#x17E;˘ The collective intelligence concept translates in a CC context as the coming together of individuals on the CC platforms and putting together their knowledge, information, and experiences about places they rented, about hosts, and even about the CC platforms, creating knowledge communities that can ultimately leverage the combined expertise of their members. These knowledge communities are represented in particular by on-site communities, which are voluntary and based on tactical affiliations and allow the relationships between companies and consumers to become a bottom-up consumer driven process where consumers take the power of media into their hands, rather than a top-down corporate driven process of controlling media content. â&#x17E;˘ The participatory culture concept refers in a CC context to the desire of individuals to recreate traditional communities and to maintain control and participate in their media world, fostering a balance between self-interest and the good of the community. This is seen in the usersâ&#x20AC;&#x2122; 50

participation where they are creating content, e.g. the numerous videos to illustrate their own personal CC experiences. ➢ The media convergence concept translates into the interaction seen between the different media forms and platforms, looking at the media technologies usage allowing for a match to the users situated context. On all accounts the CC companies had a higher usage percentage of media technologies than did the hotels and hostels. Key Numbers: ➢ 958 Hotels with a room capacity of 54,833. Mainly use Facebook and TripAdvisor. The majority (71%) applies responsive designs, but only 28% have an app that works for both iOS and Android. Just 14% have on-site communities and there is no user-generated content. ➢ 114 Hostels with a room capacity of 3,531. Mainly use Facebook, Google+ and TripAdvisor. The majority (83%) applies responsive designs, but only 14% have an app that works for both iOS and Android. Just 17% have on-site communities and there is no user-generated content. ➢ 10 CC Companies with a room capacity of 80,005. Largely use all social medias and have their own ratings systems, rather than TripAdvisor. All apply responsive designs and 50% have an app that works for both iOS and Android. Just below half (40%) have on-site communities and user generated content is currently at 10%. Key Findings: ➢ The findings show that CC companies are better at utilising media technologies than traditional hotels and hostels. This provides an advantage for the CC companies in the accommodation industry operating in Denmark, as the process of convergence culture strengthens the relationship between customer and company, by allowing the users to take part in the media creation and hereby help build their own experiences.

4.2. Diffusion of Innovations Analysis Rogers’s Diffusion of innovations theory attempts to explain the process by which individuals make adoption (or rejection) decisions, where social changes are defined according to specific events that emerge within the structure and function of a social system, over time (Rogers, 2003:11). To further demonstrate how diffusion is occurring in CC this section analyses three of the main elements related to the innovation-decision process, i.e., (1) knowledge [the social system and adopters], (2) persuasion of perceived values of CC and (3) the decision mechanism of CC, meaning to accept or reject CC companies.

4.2.1. Knowledge - The Social System Variables of Collaborative Consumption The first stage of the innovation-decision process is the part where individuals learn about the existence of a specific innovation and come across or voluntarily seek for more information about how it works. Rogers (1995:165) refers to it as the knowledge stage, and here the consumer focuses on answering some basic questions, such as 'What is the innovation?', 'How does it work?' and 'Who is using it?'. Starting from these questions, this section will look into the ways individuals got their knowledge about the CC phenomenon as an innovation, by determining what kind of information they can reach and where they can access that information about CC, more specifically from which communication channels they learned about this trend, its use, and benefits. The most rapid and efficient way to communicate about an innovation and create knowledge-awareness is considered to be using the mass media channels and interpersonal channels (Rogers, 1995:18). In the case of CC, the knowledge about this phenomenon is gained through both mass media and interpersonal communication channels. However, CC companies but also Rogers (1995:18) have observed that interpersonal channels involving direct contact are more effective in persuading individuals about an innovation. Moreover, Rachel Botsman and Roo Rogers mention the statistics from the US Department of Commerce, which say, “only 14% of people trust advertisers, yet 78% of consumers trust peer recommendations” (Botsman and Rogers, 2011:203). In addition, the very fact that the “new media technologies enabled the same content to flow through different channels and assume many different forms at the point of reception” (Jenkins, 2006:11), resulted in a variety of communication channels where individuals can share and get knowledge from.

These are exactly the considerations Airbnb used to let individuals know about their business and the opportunities users can have if using their Internet-based platform. One of Airbnb’s founders, Nate Blecharczyk, mentions that “We couldn't have existed ten years ago, before Facebook, because people weren't really into sharing” (The Economist, 2013), but that is not a problem anymore due to the Internet and users developing a growing desire “to share things when [they] surf across something interesting. (…)[They] share links, and [the] services that bring people together around common interests are growing by the day” (Media Evolution, 2012). P2P recommendations and suggestions are what fuel the sharing of knowledge about the CC trend. One easy way to just find more information about the trend is enabled through social networks, such as Facebook. For instance, on the Airbnb website, users are not required to connect their account to their Facebook account. However, if they do, the platform will show them which of their friends have been using or recommending Airbnb and if they have friends in common with Airbnb hosts (The Economist, 2013). This generates information sharing about the existence of CC platforms, going even deeper to providing information in the form of reviews from other peers about the different accommodation offers and hosts. David Lee, an early investor in Airbnb, states, “thanks to social media, people are generally more comfortable meeting new people using technology (…). Providing a secure platform for financial transactions is vital, (…) but creating a trusting community is just as important when it comes to attracting users” (The Economist, 2013). Individuals that seek more information, peer reviews, and opinions can again make use of social networks, where almost all of the CC companies present in Denmark have business pages and profiles on Facebook, Twitter, Instagram, Google+ (See Appendix V, p. 99). While users can get more basic information about what the different CC companies offer, these social networks also include peer opinions, feedback, and complaints about their services. Moreover, individuals seeking general information about how these services work, what needs to be done in order to rent or host as a CC user, can find all the knowledge they need on the CC companies’ official websites. There, it was found that most of the CC companies involved in the research have available either a guideline for the community and setting up a profile (e.g. HomeExchange, Roomorama), or an on-site community or forum where users can easily communicate (e.g. Airbnb, Couchsurfing, HomeAway) (See Appendix V, p. 99).

In addition to getting answers for how it works, users can also read testimonials and member stories from others (e.g. FlatClub, HomeExchange), which can give them more insights and ideas. Lastly, users get additional insights from the YouTube videos shared by both CC companies, and random hosts and guests of CC accommodations (See Appendix V, p. 99). In order for all this knowledge to spread out to individuals, the social system plays an important role. The social systems as defined by Rogers integrate all members that “are engaged in joint problem solving to accomplish a common goal” (Rogers, 1995: 23). They are united under the same values and norms, with a growing desire to be active participants in their lives, have more control of their world, and recreate the old trustworthy communities where sharing and collaboration created the basis for relationships (Botsman and Rogers, 2011). These are the same characteristics that Jenkins (2006) mentions for the communities that form around a participatory culture and a sense of collective wisdom that is valued among community members. Here it is important to mention that within the social system, the adoption or rejection of CC happens as a result of the individual’s decision, and not as an entire social system of members. Therefore, individuals who come across this innovation (i.e. P2P CC) voluntarily enter in to the social system and adhere to its values and norms while engaging in CC practices.

4.2.1.1. Characteristics of Collaborative Consumption Adopters The segments that make up the social system, or in other words the communities of CC, are a mix of different generations, though with a shared set of motives, norms, and values. Identifying the characteristics of the CC adopters provides general insights on the types of individuals that choose to adopt the trend. Botsman and Rogers describe the millennials as the generation that was born digital and as a segment that is not defined by age - these are the sharers. However, they also state that CC is not at all only confined to the millennials, but that this group is known as being digitally savvy, why they will naturally be the initially dominant group within CC (Botsman and Rogers, 2011:60). Lisa Gansky expands the demographics as described in Zimmerman’s article on CC (2012:3) stating that “Demographically, the sharing economy started with the Gen-Y, mostly those in their 20s and early 30s who participated in it to save or earn money in response to the recession”, but explains how the trend has now spread to Gen-X and baby boomers too. She herself is 53 and provides an example of Kepa Askenasy, aged 56, who rents out rooms at her San Francisco property and experienced hosting individuals of ages ranging from 19 to 90 (Zimmerman, 2012:4). 54

This corresponds with the findings from an American national consumer study (Mithun, 2012) where it was found that 62% of Gen-Xers and Millennials found the general concept of sharing appealing, but the Gen-Xers overtook the millennials with 31% (vs. 24%) regarding the CC concept as ‘very appealing’. Boomers had the lowest percentages with 53% thinking the concept was ‘appealing’ and only 15% ‘very appealing’. Likewise a study from Ipsos Public Affairs (2013) further defined these demographics by showing that “Adults under the age of 35 (30%) are much more likely to report that they have shared something online with someone they didn’t previously know than are those aged 35-54 (15%) or 55 and over (8%). In addition to younger adults, men (21% vs. 14% of women), those with children in the household (23% vs. 15%), and those who are not married (20% vs. 15%) are also more likely to have shared their property or belongings online.” The study also shows that within the interviewees that had not yet participated in CC, fewer were open to sharing a room in their home than renting out skills or tools and in general women and older adults felt wary of sharing their home. Furthermore Airbnb, based on their own data (Airbnb no. 3, 2014), state that 50% of their users have a moderate to low income and 47% have thus used the income gained from the site to ensure that they could stay in their homes. Additionally, Airbnb state that the site has a positive economic impact as 76% of the Airbnb properties are outside the main hotel districts and on average stay 5 nights while a typical tourist generally stays for 2.8 nights. 50% of the guests spending is supporting the local neighborhoods they stayed in and that they on average spend 6,040 DKK compared to a typical tourists spending of 4,135 DKK.

Figure 15 - General Characteristics of CC Adopters (Own model, 2014) The characteristics of the individuals that have adopted CC and make up its social system are thus a majority of younger adults, with the trend spreading to older generations as well. In general men are more likely to share than women, single people more often than married and along with those with children in the house. The latter though relates to sharing of belongings, e.g. childrens clothes and toys, rather than property. The CC guests also tend to stay longer and spend more. All of these personas share a set of social norms of a necessity to share and thus make better use of available resources, as Lisa Gansky puts it â&#x20AC;&#x153;Value unused = waste. [...] In natural systems, waste is never wasted. In nature, â&#x20AC;&#x153;wasteâ&#x20AC;? from one system is food for another. The challenge in business is how to retrieve 56

value from waste of all types, such as idle cars or equipment. It’s finding value products that can be repaired rather than earmarked for the dump. The Mesh invites and enables the recovery of that “waste” as value” (Gansky, 2010). The more specific values of this social system relates to the perceived advantages of CC discussed in the following section.

4.2.2. Persuasion - The Perceived Values of Collaborative Consumption This section pinpoints the perceived consumer values of CC as identified in various articles and by the main experts within the field, Botsman (2011) and Gansky (2010) and in accordance with Everett Rogers’ defined characteristics of an innovation (Relative advantage, compatibility, complexity, trialability, and observability - See p. 15). Finding these value generating attributes will enable further research into the question of why the trend of P2P CC is diffusing among consumers and provide insights for the traditional players in the accommodation industry. The typical relative advantages suggested by Rogers (1995); economic profitability, social prestige, savings in time and effort, decrease in discomfort, and immediacy of the reward correspond to the motivations that Botsman and Rogers (2011:173) describe in their book. In both a small pilot project and through their general research they identified the following four overall CC attributes as being the most important for CC consumers in general: 1. Cost savings 2. Coming together 3. Convenience 4. Being more socially conscious and green The latter relating to environmental friendliness was however usually never the main reason for neither the consumers nor the entrepreneurs starting the CC businesses (Botsman and Rogers, 2011:98). Given that fact and the focus on the accommodation industry in this study, further research within the topic of environmental friendliness will be omitted. Though it should be mentioned that it is often considered a side benefit that does give both emotional gratification and heightened social prestige (Botsman and Rogers, 2011). Likewise convenience is largely associated with the general concept of sharing in CC relating to the idea of access over ownership and is thus more important for e.g. car sharing, sharing of tools, etc. The convenience factor is not viewed as a specific relative advantage for the CC accommodation industry, as all accommodation companies offer access over ownership by renting out rooms, apartments, houses, etc. Convenience in the form of accessibility 57

through various platforms and the ease of use of these media technologies are, however, considered as relative advantages by CC users (Piercey, 2012).

Figure 16 - Cost saving comparison chart (Own model, 2014) Cost savings was at the top of the list, which has also been identified as a main attribute in other quantitative surveys on the subject (Mithun, 2012 and Owyang, 2014). It is however, important to note that there is a lack of availability in data of actual spending on accommodation offerings, why the data is focused on the prices offered by the various players (See Appendix VII, p. 107). The data collected for this study shows that the individuals choosing to rent a place from a CC platform can save a considerable amount of money, in comparison to renting a place at a hotel or a hostel. Here it is important to mention that some CC platforms work on a free rental or exchange basis. For instance, on Couchsurfing homestays are consensual between the host and the guest, with no monetary exchange. Another example is HomeExchange, where users exchange their homes for free, with the sole cost of having a membership on the CC platform, of 740 DKK per year. Furthermore, while the other CC platforms include in the cost of the accommodation the rent for the place and sometimes an extra fee, in the hotel and hostel cases there are many hidden costs besides the actual rent. For this study, the hidden costs that have been added to the cost of the accommodation include breakfast, bed linen, towels, and mandatory administrative charges. The reason for including these hidden costs is that they represent amenities that CC users benefit, without any additional costs. Thus, as the chart above shows, there are considerable cost savings between hotels and CC companies, as all of the low costs for renting a room at the hotel exceed the low costs for the CC companies. Moreover, even though some hostels seem to be at a lower cost than the CC companiesâ&#x20AC;&#x2122; offerings, the research shows that the conditions at the hostel places differ considerably from CC accommodation offerings, because individuals can sometimes only get a bed in a shared room with seven, nine, or even 65 other persons,

and share a bathroom with all other hostel guests. In contrast, the CC accommodation offerings include either the entire place or a shared room with access to all facilities like bathroom, kitchen, and living room, but still having the privacy of an individual room just for the guest. This advantage is clearly a factor that the CC companies try to make consumers aware of, with slogans like: “Book a whole home for less than the price of a hotel room” (HouseTrip no. 1, 2014) and “Simply Better Than a Hotel – Up to 50% cheaper than a hotel” (Wimdu no. 1, 2014). Also with these CC accommodation companies there is the new option to haggle about the price, since you can chat or email directly with the host (Gansky, 2010:20). One of the greatest advantages for hosts is the newly added benefit, enabled by the CC companies, of having an extra income from renting out their apartment or room. This is what makes the phenomenon of CC stand out as it potentially allows anyone with an Internet connection to become a business player. Lisa Gansky provides an example of a woman earning 8,000 USD in a year by renting out her New York City apartment while she was travelling (Zimmerman, 2012:4). Similarly a Norwegian woman has earned close to 8,100 DKK a month from renting out a room in her Oslo apartment (Fogde, 2014) and Wimdu states that their hosts on average earn 6,700 DKK per month (Wimdu no. 2, 2014).

Figure 17 - Monetary Distribution for Airbnb in Denmark (Adapted from Toft no. 1, 2014) Of course the income will vary considerably depending on how often one rents out, the amount of rooms one has available to rent out and the location of the rentals. This, however, relates to another 59

advantage; idling capacity as Botsman and Rogers (2011:83) have dubbed the term, which relates to making use of items, or in our case, space that is owned but rarely used. One relative advantage that specifically relates to the CC companies in the accommodation industry and seems to be the most important is that it is more authentic travel and not just a typical tourist stay. Casey Fenton, the founder of Couchsurfing, established the company based on this notion: “I did not want to pay for an expensive hotel or play Mr. Tourist in a youth hostel” (Gansky, 2010:176) and further explains that the motivation behind the company is “Living with locals, living their life” (Gansky, 2010:177). This factor is visible in almost all of the CC companies as either part of their slogans or descriptive text: “Rent unique places to stay from local hosts” (Airbnb no. 4, 2014), “There's more to travel than visiting a checklist of tourist attractions” (Roomorama, 2014), “Travel your way and live like a local” (HomeExchange no. 2, 2014), and “Rent from a local and enjoy a more comfy, personal and affordable world” (9Flat no. 1, 2014). Airbnb even have statistics based on their own data (Airbnb no. 3, 2014) stating that 89% of their users want to “live like a local”. Furthermore there are the added benefits at no extra charge that relate to renting someone’s home rather than a standardised hotel, as HouseTrip for example points out on their website “Enjoy the many benefits that holiday rentals have to offer: more space, extra bedrooms, a kitchen and WiFi and laundry facilities at no extra charge” (HouseTrip no. 2, 2014). Apart from the extrinsic rewards, there is also the intrinsic reward of emotional benefits that come with sharing, which trigger affirmation and belonging in individuals, making the generosity to oneself and others an important part of participating in CC (Mithun, 2012:1). As Botsman (Piercey, 2012) puts it “So, there’s the self-interest but part of the beauty of the movement is that the self-interest is paired with community and a social mind-set”, the ‘coming together’ which is so highly valued by CC participants. The ability to haggle about the price, as mentioned earlier, relates to this as the communication takes place directly between host and renter, with the CC company merely acting as broker, facilitating the interaction. The more direct and personal communication along with the distrust in big brands in recent years is making people more willing to try new brands and lifestyles (Gansky, 2010:45). As such the coming together creates a community where typical top-down ‘command and control’ is removed and trust between strangers is enabled (Botsman and Rogers, 2011:91). Ratings, disagreements, and enforcement of the rules are largely resolved within the community itself, as the reputation systems facilitated by the Internet create a perceived fairness that everyone must abide by if wanting to continue to be part of that community, as a bad rating will most likely mean less rentals (Botsman and Rogers, 2010:140).

The compatibility is seen in the intrinsic factors, emotions, community feeling, trust which correspond with the existing values of potential adopters. CC is not at its core a radical and new to the world innovation and consumers will have had past experiences resembling this and especially in the accommodation industry, past examples with bookings and travel will not differ profoundly. The CC option also fits with the needs of the potential adopters as described earlier, the cost savings were deemed the most important by consumers, which is also highly driven by the economic crisis (Botsman and Rogers, 2011) and also the wish for more authentic travels. The learning curve or complexity to get started with a site such as Airbnb is not very steep, all the sites look very much alike (See Figure 18) and anyone with a little past experience with online booking and an online profile somewhere, should be able to navigate the sites to either rent or become a host. If difficulties still exist, there are numerous instructional videos and explanations both on the sites and on YouTube (Airbnb no. 2, 2014, Wimdu no. 1, 2014, GoddessFreya1970, 2012, and Varga, 2013).

Figure 18 - Similarity Between CC Companiesâ&#x20AC;&#x2122; Websites Lowering Complexity (Own image, 2014) With regards to trialability, most of the sites are free to use, when creating a profile, with the host paying a percentage of the rental fee to the company, like in the case of Airbnb where there is a service fee of 3% (Airbnb no. 6, 2014). The sites are as such easy to test out to lower the uncertainty

for the individual. Others offer trial periods like HomeExchange, which have a free trial period of 14 days and after that have a membership fee of 740 DKK a year (HomeExchange no. 1, 2014). Observability of CC is easily detected, as the phenomenon is often mentioned in news, articles, customer reviews, and general word-of-mouth. As mentioned earlier the result of the innovation is, in this case, for many people the added income or an authentic journey and these are easily observed and shared. The features of CC seem to appeal to consumers worldwide and Airbnb could at the end of 2013 report that it, since its launch in 2008, had reached a total of 10 million stays. A growth rate that further illustrates that the CC trend is not only for adventurous and young early adopters with a budget to maintain, but rather a new world of shared travel focused on social and economic factors (Velikova, 2014).

4.2.3. Decision - Adoption or Rejection of Collaborative Consumption Initially Couchsurfing was the only CC Company available in Denmark, and the other nine have entered the market over the past six years. This clearly indicates that CC in the accommodation industry is a relatively new phenomenon in Denmark, showing a high level of growth (See Appendix VIII, p. 108).

Figure 19 - Growth in Amount of CC Accommodation Companies in Denmark (Own model, 2014) Â There exists a lack of availability of data regarding actual number of members of the various CC companies. Therefore Airbnb, Couchsurfing, and HomeExchange, the best known, and three of the largest CC players on the Danish market, will be used to represent the user adoption of the alternative accommodation industry.

Figure 20 - Growth of CC Users by Available Rooms in DK (Own model, 2014)

As figure 20 illustrates Couchsurfing has experienced exponential growth of users in Denmark. Airbnbâ&#x20AC;&#x2122;s growth has been slightly less rapid but has also only been available in Denmark half the time and is a paid service, as opposed to Couchsurfing, which is free. Whereas HomeExchange has experienced a small but steady growth in Denmark (See Appendix IX, p. 108). It is important to be aware of the fact that there is no guarantee that users do not have several profiles or listings, thus data on the exact amount of available rooms can be skewed. However, even though many experts have raised the concern that landlords would exploit the opportunities of the CC accommodation providers, this is not yet the case in Denmark. In fact 79% of the Danish Airbnb users only have one listing and as few as 10 users have more than 10 listings. These 10 users were identified to be small companies, such as a camping site and B&B establishments, using Airbnb as a marketing channel (Toft no. 2, 2014). In Denmark the distribution of available Airbnb apartment listings is spread all over the country, with the highest densities in the larger cities and the vast majority located in Copenhagen. Â

Figure 21 - Distribution of Airbnb Available Apartments in Denmark (Toft no. 2, 2014) Note that available private, shared, B&B rooms, etc. are not part of the illustration.

These numbers, along with the fact that new members are signing up to the CC companies almost every day shows that the phenomenon has reached what Botsman and Rogers call ‘critical mass’. Critical mass is the tipping point of popularity for a CC offering and happens when consumers are satisfied with the amount of availability to fit their needs and choices and when there is enough social proof, meaning “everyone else is doing it”, leading to a larger majority also being ready to engage with it (Botsman and Rogers, 2011:80-82). Over a period of just one month, during the writing of this report, the total number of members has risen with 3,997 (See Appendix X, p. 109). Another way to assess the current adoption of the CC accommodation industry in Denmark is to look at the growth through the rise in amount of overnight stays over the last few years (See Appendix XI, p. 109).

Figure 22 - CC Growth by overnight stays (Own model, 2014) Overall, only a small amount of users have yet adopted the alternative accommodation industry that is provided by the CC companies. The overnight stays, amount of new CC companies, and members are, however, growing at exponential rates, meaning that the CC phenomenon is definitely gaining traction in Denmark.

4.2.3.1. Rate of Adoption of Collaborative Consumption in Denmark The adoption rate will explain how the CC phenomenon within the accommodation industry has and will spread through the Danish society. The previous paragraphs have investigated the factors that, according to Rogers (2003:222), have an influence on the rate of adoption - the variables within the Innovation-Decision Process (See p. 14). The relative advantages as perceived by the consumers of the innovation are the most important factor of the rate of adoption (Rogers, 2003:233). The more positive the perceived advantages are the faster the rate of adoption is. When compatibility between the innovation, the individual users', and the social systemâ&#x20AC;&#x2122;s norms and values exist, complexity is lowered, trialability is possible, and observability is present, as in the case of CC, meaning that the rate of adoption is sped up (Rogers, 2003:266). The use of interpersonal channels, rather than mass media channels for creating awareness-knowledge, which is often the case for later adopters, slows down the rate of adoption (Rogers, 2003:222). Both mass media channels (news, articles, etc.) and interpersonal channels (social media, forums, communities, etc.) have been utilized to spread the word of Airbnb, which has meant that the communication has positively affected the rate of adoption of CC in Denmark. The optional type of innovation-decision, which means that it is up to the individual to decide whether to adopt or not, as in the case of CC, speeds up the rate of adoption (Rogers, 2003:29). So according to Rogersâ&#x20AC;&#x2122;

theory all the variables determining the rate of adoption are in this case positive for CC, meaning that there should exist a high rate of adoption in Denmark. However, Rogers does not provide a specific formula for calculating the rate of adoption, therefore in order to calculate this, additional inspiration has been found from a management consultancy firm, that presents an approach for calculating the adoption rate (8020 World Management Consulting no. 1, 2012). Furthermore, it is important to note that the rate of adoption will always be a guestimation as it aims at predicting the future and as Rogers (2003:213) explains “Such measurement is often impractical or impossible because the confirmation stage may continue over an indefinite period. (...) The period is thus a gestation period during which a new idea ferments in an individual’s mind”. Since Airbnb is the most widely discussed CC accommodation company in Denmark, making the availability of data higher, the rate of adoption of CC in Denmark will be calculated through the use of this data. Airbnb entered Denmark in 2010 (See figure 19, p. 62) and could by the year of 2014 report a growth of 95% in amount of listings in comparison to 2013 (See Appendix I, p. 93). This hypergrowth of 95% YoY (Year over Year) further verifies that the alternative accommodation industry of CC has reached critical mass becoming self-sustaining and providing enough choice to satisfy the users’ varying choices and needs.

Figure 23 - CC Adoption Rate in Denmark (Own model, 2014) 66

The calculation of the adoption rate in Denmark was thus based on the 95% growth rate YoY, which was used to determine the increase in listings from the current amount of 13,403 (See Appendix XII, p. 110). Since Airbnb describe themselves as “(...) a trusted community marketplace for people to list, discover, and book unique accommodations around the world ” (Airbnb no. 1, 2014), the maximum of possible accommodations in Denmark was identified. There exist 2,745,000 (Danmarks Statistik no. 4, 2012:7) available apartments and houses in Denmark, which in the calculation make up the 100% of possible adopters by listings. Typically the saturation is set to 90%, the highest value that the top of the s-curve can reach before it starts to plateau (8020 World Management Consulting, 2012). Though in the case of CC this number would be rather high, since the identified characteristics of CC adopters revealed that married couples and older generations are less likely to adopt. Hence the market saturation was in this case set to 70%. This means that if Airbnb were to reach 70% of the possible listings in Denmark, they would have 1,921,500 listings on their site, thus saturating the market by reaching the highest amount of feasible adopters. In short the rate of adoption of CC in Denmark is growing at a high speed. If this growth rate of 95% was to continue Airbnb would saturate the market in approximately 8 years in 2022 (See Appendix XII, p. 110). The phenomenon of CC has as such presented consumers with decreased costs and increased accessibility, which has the potential to transform entire industries, as described in Christensen’s Theory of Disruptive Innovations and which will be analysed in the next chapter (Wanamaker and Bean, 2013).

4.2.4. Diffusion of Innovations Analysis Chapter Takeaways Diffusion of Innovations Theory: ➢ The knowledge of CC is gained through both mass media and interpersonal communication channels of which the latter has played a major part in the P2P knowledge sharing, as it tends to be more trusted. The social system works toward a common goal, values having more control, and that sharing and collaboration are at the basis of the relationships of the communities. This has been further enabled through social media and has provided easy access to added information, peer reviews, and opinions. The individuals within this social system follow the norm of “Value unused = waste”. They currently tend to be younger adults, mainly men, and singles.

➢ The perceived values that drive the persuasion towards CC are cost savings, as individuals that rent a place from a CC platform can save a considerable amount of money. Convenience in the form of accessibility and ease of use through media technologies, added income, more authentic travel moving away from a typical tourist stay, and coming together through trust between strangers. All of these make CC compatible with the existing values of the social system and individuals within. Additionally the low level of complexity, possibility of trials and high level of observability all lead to positive persuasion on the decision to adopt. ➢ The decision of adoption of CC in Denmark is currently still low, though new members are signing up to the CC companies almost every day. The overnight stays and amount of members are growing at exponential rates, along with several new CC companies entering Denmark, meaning that many people have started to make the decision to adopt CC. Key Numbers: ➢ The total number of members has risen with 3,997 in just one month, during the writing of this report. ➢ Airbnb reached 500,000 overnight stays in Denmark and HomeExchange reached 130,000. ➢ Airbnb currently has a growth rate of 95% YoY, if this growth rate was to continue Airbnb would saturate the market in approximately 8 years in 2022. Key Findings ➢ The findings show that CC has reached critical mass in Denmark and the rate of adoption is growing at a very high rate.

4.3. Disruptive Innovation Analysis This section briefly reintroduces Clayton Christensen Disruptive Innovation theory to address the following question, using performance measures and trajectories: ‘How and why is the trend of peer-to-peer collaborative consumption diffusing among consumers disrupting the traditional business players in the Danish accommodation industry?’ The hotel industry has been a challenge for Christensen's theory because, according to the author, the industry had yet to see any disruptive changes in its core competency that allowed upward mobility in the market (Christensen in Blodget, 2014). However, with the introduction of a new business model that uses the disruptive technology in P2P platforms, that grants ordinary people the ability to share and market rooms for profit, the accommodation sector is now undergoing possible market transference. In other words, the CC companies’ ability to challenge market leaders traditional source of supply by enabling anyone with a couch to run their own B&B service (Staff, 2013) set in motion a disruptive movement within the industry. Furthermore, users of CC services are not booking with a company per say but with another person. For example, Airbnb allows its users to create and promote their own dynamic pages in order to let potential guests know about the types, location, and availability of rented accommodations (Airbnb no.5, 2014). According to Rachel Botsman on the issue of CC companies, she states, ”Thus far, the “biggest disruption” is by Airbnb to the hotel industry: “By the end of [2012], they will be filling more rooms per night than Hilton. That is serious disruption” (Berelowitz, 2013).

4.3.1. Comparison of the performance trajectories As an incumbent, the traditional hotel industry’s performance attributes are based on an industrial model whereby having a great location, a targeted market segment, a theme, and a high occupancy rate would be enough to differentiate one hotel from another. However, CC companies are causing what Christensen has defined as, both low-end and new-market disruptions in the industry, resulting in hotels taking ‘a wait and see position’ to determine if this movement is a fad or a real threat (See Figure 29, p. 75). For example, lower-tier hotels are disrupting the incumbents by altering the competitive force using performance features of low cost, trust and reputations mechanisms through the use of media technologies. Similarly, new market disruption from Airbnb, Wimdu, and HomeExchange use identical performance features such as booking technology and online user communities as their value propositions. These features are thus fast becoming more valuable than what the market is already experiencing especially when traditional hotels are recognizing their vast potential of direct messaging between hosts and guests. Moreover, 69

CC companies have proven the ability to build trust between members and users of their services as evident by their success among users. In contrast, traditional hotels performance attributes, are so far customer service, safety, value added packages, and Wi-Fi. Their use of media technology has shown to lag behind those of CC even as they add more emphasis with the use of social media as engagement platforms and ratings. Considering that occupancy rate is often linked to the measure of performance in for example value added packages, goes along the lines of explicitly defining the disruptive nature of the y-axis, of the disruptive strategy model, in the accommodation industry. Therefore by looking into the Danish accommodation industry number of overnights stays and occupancy rate offers insights into if the CC companies are impacting the traditional sector and what the traditional sector can do to regain market share with value propositions.

4.3.2. Collaborative Consumptionâ&#x20AC;&#x2122;s Disruption on the Danish Accommodation Industry Over the past 10 years the total amount of overnights stays at hostels has been rather stable in Denmark with an increase of 124,627. The hotels have on the other hand experienced an overall growth of an extra 3,170,353 overnight stays, with the exception of the financial crisis that affected the hotels the most in 2009, facing a decrease of 681,529 overnight stays compared to before the crisis began (See Appendix XIII, p. 111).

Figure 24 - Total Amount of Overnight Stays at Hotels and Hostels in Denmark (Own model, 2014)

In Denmark the distribution of the capacity in the accommodation industry in 2014 looks as follows:

Figure 25 - Difference in Amount of Rooms in Denmark by Accommodation Type (Own model, 2014) This adds up to a total of approximately 138,419 rooms available in the Danish accommodation industry, when focussing on hotels, hostels, and the CC companies. Even though the CC companies have the highest availability of rooms, they have not yet overtaken the hotels in the amount of overnight stays (See Figure 26). They have though overtaken the hostels, which fits with the Disruptive Innovation theory prediction that it is initially the low tier offerings that are displaced. It is, however, important to mention that the data on overnight stays for the CC companies is based on an estimation. Due to a lack of available data for the smaller CC players and the reluctance to share any data from others, the estimation has been based on the available data from HomeExchange. Here data on growth throughout the years has been available, why these numbers have been applied as a guideline for the correspondence between listings and overnight stays for the remaining CC companies (See limitations p. 33 and Appendix II, p. 94).

Figure 26 - Difference Between Overnight Stays in 2013 (Own model, 2014) 71

“It is clear that although the overnight stays in hotels has increased, it is not by 150 percent, as it is with Airbnb, and one must admit that they now have a slightly higher market share than in the past,” said Jens Zimmer Christensen the chairman of HORESTA (HORESTA no. 2, 2014). In December of 2013 the impression was however quite different, with Katja K. Østergaard, CEO of HORESTA, denying that Airbnb was a significant competitor to the Danish hotels, further stating that: “One day you wish to stay at a five star hotel, the next day the authentic experience of staying private. There are many aspects of tourism today. If, or when, Airbnb is a serious competitor to the pressed Danish hotel industry HORESTA will require that competition takes place on equal terms. It is only natural when there is a kind of professional rental of private homes” (HORESTA no. 3, 2013) In August 2014 after Airbnb had experienced the growth of 150% in just that year, the tone was again different: “There is now an offering of 10,000 rooms (houses) in Denmark [via Airbnb]. Coupled with a range of approximately 49,000 hotel rooms, the supply of private rental systematized through Airbnb has thus become quite high and is still rising. We of course welcome the competition and are pleased that more and more international tourists choose to travel to Denmark. Airbnb as a concept provides tourists with more options and can also drag a type of guest here who may not otherwise have come. It strengthens the brand awareness for Denmark, which means more guests in our restaurants and attractions etc., And the next time the tourists come here, they may choose to stay in a hotel instead.” (HORESTA no. 4, 2014).

These statements clearly indicate the beginning effects that CC companies, such as Airbnb, are having on the traditional players in the accommodation industry in Denmark. This factor is not only applicable to the Danish industry: “The hotel industry is sending mixed messages about the competitive threat of Airbnb. While they are publicly quoted as saying they are not concerned, they are also exploring legislative options against shared housing services such as Airbnb” (MIT Sloan EE, 2014). Consequently, many countries and government institutions have started conducting or considering legislative action toward CC companies in various sectors (Torregrossa, 2013) that are changing essential parts of the businesses, such as the subscription models. The subject has also been widely discussed in the media in Denmark, with official sources claiming that it was illegal to rent out your apartment through Airbnb, as stated by Jesper Larsen, Chief Economist at The Tenants Union in Denmark (LLO) “If you rent your apartment out a few weeks a year, it's against the rules for the use of housing. They must be used 72

for housing and not as hoteliers” (Hansen, 2013). Some even went as far as to say that renting out your apartment on Airbnb could put you on the street (Flach, 2014).

However, in late 2013 it was announced on DR, by the correct authority (Housing Minister Carsten Hansen), that it was in fact not illegal to rent out your apartment through Airbnb, as long as certain tax laws were followed (Nielsen, 2013). This statement was also posted on Airbnb’s own public policy site; “It is not illegal to rent one’s house out, when you go on vacation, says Housing Minister Carsten Hansen. There is no reason to be worried…it is both perfectly fine with me and with the law” (Hantman, 2013). The Housing Minister continues the explanation with "As long as you stick to less than 6-7 weeks a year, anyone is free to rent out their own accommodation to tourists" (Bolius, 2014). HORESTA maintains that the alternative accommodation providers should be subject to the same requirements as the hotels and should thus also be required to report the landlords income tax and record the number of overnight stays (HORESTA no. 5, 2014). Both HORESTA and VisitDenmark are interested in Danmarks Statistik registering private stays of tourists, in order to calculate their impact (Kjær, 2013). The discussion on exactly how to regulate is still ongoing, with HORESTA calling for more regulations to ensure that Airbnb and others operate within the law (HORESTA no. 6, 2014) and the CEO stating that “When there is competition in the market, it must also be fair that it is conducted on similar terms as the established businesses are operating under now. (...) first and foremost have individual registration so you know who lives where and when. And then the lease should be taxed” (HORESTA no. 7, 2014). It is therefore very important to mention these legislative impacts as they can ultimately change both the construction of the CC companies and the impact that they have on the industry in Denmark.

These regulatory impacts are typical signs of disruptions that occur when traditional players in an industry are faced with growing new entrants and thus try to block the disruptive approaches. “But even if existing companies miss the disruptors’ arrival, they can still slow the inevitable transformation of their business by engaging the legal system. Firms that are constrained in their own ability to innovate by regulatory restrictions, for example, can urge their regulators to force the disruptors to play by the same rules, a strategy that has tripped up start-ups including Uber , Airbnb and Tesla.” (Downes and Nunes, 2014).

4.3.3. Actual Market Share Loss in Traditional Danish Industry In terms of the actual impacts that the alternative accommodation industry is having in Denmark the market share distributions have been identified as follows for the hotels, hostels, and CC companies:

Figure 27 â&#x20AC;&#x201C; Market Share Distribution Based on Current Overnight Stays (Own model, 2014) This amounts to a total of 15,942,730 overnight stays within the Danish industry in 2013. Interestingly enough this actually only accounts for a third of the maximum capacity of 50,522,935 rooms offered by the 1,082 competitors in the accommodation industry in a year (See Appendix XIV, p. 112). In comparison the total amount of overnight stays in 2012 was 14,177,756.

Figure 28 - Market Share Distribution Based on Overnight Stays in 2012 (Own model, 2014) 74

When comparing the market share distribution of the two years it is clear that the whole market has grown as the total amount of overnight stays has increased with 1,764,974 (See Appendix XV, p. 113). The decrease in market shares for hostels and hotels can as such be attributed to the CC companies’ arrival, as there is market share loss, though through new market creation, which also corresponds to Christensen’s description of new-market disruption.

Figure 29 - Industry Disruption (Based on Christensen and Raynor, 2003:44) The above figure represents both low-end and new market disruptions. The low-end disruptors are the lower-tier hotels and hostels. They offer specific benefits to the least demanding consumers by being less-expensive, more convenient and simpler, with the potential of eventually reaching mainstream users and replacing hotels as market leaders. Their disruption follows the basic premise of Christensen’s theory in that the lower-tier hotels, labeled by incumbents as an inferior product creates disruptions in the industry. Even though lower-tier hotels created a disruption the data however 75

demonstrates that in fact no replacement of the market leaders have yet to happen (Markides, 2006:21). Thus raising doubt, at least in this study, on one of Christensen’s conclusions about how disruptions typically dethrone incumbents. CC companies, e.g., Airbnb, HomeExchange and Couchsurfing are new market disruptors that entered the market using a novel value proposition resulting in the creation of a new market segment; one that is different than what is available in the accommodation industry. Moreover, the CC companies are able to exploit the disruptive nature of P2P platforms by establishing trust with the permission of mutual viewing of approved user profiles for marketing purposes as well as the booking of available rooms/couches effortlessly. Furthermore, because trust is the ‘currency’ of P2P accommodations (Botsman, 2012), CC companies have overemphasized the importance of their rating and review feature mechanisms. Moreover, the CC companies have transformed the market by successfully building a strong relationship with millennials, yet they have not neglected the benefits of GenXers or Boomers. In contrast, the market loss experienced by the traditional sector is noticeable within the millennial segment, as they have trouble finding leverage in how to reach this group. Meaning that, hotels are finding it a challenge to market to the millennial demographic, and have conceded that Airbnb already has a grasp on them (Sell, 2014). Conley, head of Airbnb hospitality states: “I guess my response is it already exists and Airbnb has captured that market. Our consumer data on this is phenomenal and Airbnb is in this millennial generation market. We are clearly a dominant lodging brand in terms of how that generation sees us" (Sell, 2014). The following section will therefore present suggestions on how the hotel industry can attract this elusive group.

4.4. Suggestions for the Traditional Players Based on the analysis findings discussed above a set of suggestions have been developed that could help traditional accommodation providers in Denmark target the customer segment that was identified as the primary group attracted by the CC accommodation offerings. The reason for the need to generate a set of suggestions that traditional players could apply to their businesses is based on what Christensen argues in relation to traditional companies:

“One might wonder why, when new markets are developed by disruptive entrants, the typically better-funded, more resource-rich incumbents do not simply move into those new markets themselves. Focusing on this issue, Christensen had a breakthrough insight: the incumbents do not pursue these opportunities because it would not make sense for them to do so. The incumbents do not move into these markets because doing so would divert resources that could be more profitably used delivering better products and service to their best and most profitable customers" (Campbell, 2012:14-15). Thus, not being able to move into these markets is why traditional companies need to overcome this barrier by pursuing alternative strategies that attempt to attract the customers of this new created market, which is what this study offers through a set of suggestions. Moreover, Christensen further explains the reasoning behind the need of the traditional companies to adapt and keep up with the market and its customers: “(...) successful companies can be upended by new technologies that first appear as cheaper products with fewer features, but improve quickly and ultimately take over. Think personal computers vs. mainframes. But not anymore. Our research shows that especially in industries dominated by digital technology, the disruptors now arrive better and cheaper than existing goods, right from the start — think free integrated smartphone navigation apps vs. stand-alone GPS devices. “Disruptive innovation” is increasingly “devastating innovation,” or what we call “big bang disruption.” Businesses that wait for the disruptor to arrive before figuring out how to incorporate it in their products — as Christensen recommended — are already too late.” (Downes and Nunes, 2014). This is the reasoning behind this study, which acknowledges the importance that the traditional accommodation providers pay attention to the new entrants to the market and adapt to the changes that happen within the market. Accordingly, one suggestion for the traditional accommodation providers in Denmark is related to their use of media technologies to engage and interact with their users. The findings show that hotels and hostels offer limited access for their users to interact with the company and to participate in sharing their own experiences, in contrast to the CC accommodation companies who make use of the most popular platforms to interact with their users. As shown in the analysis, the process of convergence culture and the use of numerous social networking platforms, combined with offering availability through a responsive website and smartphone apps provide a strengthened relationship between customer and company, where users are able to participate in media creation and sharing. 77

Offering Wi-Fi connection, which was considered by 82% of managers and directors of hotel operations one of the most important services that consumers want when staying at a hotel (Brewer et al., 2008:2), along with use of self-service technologies (booking systems, self check-in, and in-room check-out) (Brewer et al., 2008:4), are no longer optional services. Consumers expect to benefit from these basic services and thus hotels and hostels need to improve their approach by looking at what technologies and services CC accommodation companies provide. This is also what hoteliers participating in a study agreed: "The most important goal identified by the hoteliers was to use technology to enhance the guest experience" (Brewer et al., 2008:8). Another approach that traditional accommodation players could adopt is trying to offer a more authentic travel experience for their customers. This can be done by moving away from the typical tourist stay and involving a more personalised introduction of the place that is being visited, together with suggestions for the most important touristic attractions and places where guests can go and meet the locals. Travellers want to feel more like a local and ensuring that they can actively participate in the culture they’re getting to know is a good first step in enhancing their travel experience. Additionally, another aspect that needs to be taken into consideration by traditional accommodation providers is attracting the new market reached by the CC accommodation companies, targeting first of all the millennials. As discussed in the disruptive innovation section above, the traditional accommodation players experience a market loss within this segment, and thus in order to compete with the new entrants on the market they need to adopt new strategies, such as the ones presented above, that target this segment as well. What is more, hoteliers can no longer rest assured that the alternative accommodation companies are only targeting the segment of the market looking for leisure services at low prices, as Kimpton Hotels CEO Mike Depatie seemed to believe in June 2014: “They’re heavily skewed toward leisure. We’re heavily skewed toward business. And so I think they’re going to get into that market but I’m not totally worried about them. They’re a bigger competitor for more limited service hotels at a lower price point” (Oates, 2014). As a matter of fact, business travellers in the millennial generation started to embrace the Airbnb concept as a new travel experience that can also work for business trips. This fact is also agreed by Michael Hilton, a Concur executive vice president, “They’ve had experience a few times with Airbnb and decided it’s not only cheaper than a hotel, but in a lot of cases better” (Sharkey, 2014). Therefore, hotel and hostel managers need to stop dismissing Airbnb and other accommodation providers alike, “thinking [their] listings [are] far too humble, too inconsistent, and too unappealing to 78

travelers accustomed to more upscale accommodations” (Oates, 2014), and instead recognise they can represent a threat in the long run. Michael Hilton agrees by saying: “Airbnb is an interesting trend in our customer base. It’s not a significant share of the lodging spend yet, but it’s growing exponentially and developing clearly as a choice for business travelers” (Sharkey, 2014).

4.5. Disruptive Innovation Analysis Takeaways Disruptive Innovation Theory: ➢ The performance trajectories of the traditional industry are based on industrial models merely focused on having a great location, a targeted market segment, a theme, and a high occupancy rate to differentiate the hotels and hostels from one another. Whereas the CC companies have introduced a new business model that uses the disruptive technology in P2P platforms, enabling anyone with a couch to run their own accommodation service. The CC companies have started transforming the market and creating a new market by first attracting millennials, a segment that the hoteliers state, have been hard to attract. ➢ In terms of value propositions the traditional hotels have stuck to their offerings of attributes such as customer service, safety, value added packages, and Wi-FI. In contrast the use of technology that the CC companies have applied has helped them offer a novel value proposition by establishing trust between peers, effortless booking and availability, personalized marketing options, rating and review features. ➢ The market share distribution has been altered as the CC companies enter the market as new market disruptors with their novel value proposition. Thus CC is initially disrupting the lower-tier hotels and hostels, which are consequently the low-end disruptors that offer specific benefits to the least demanding consumers by being less-expensive, more convenient and simpler, with the potential of eventually reaching mainstream users and replacing the hotels. Key Numbers: ➢ Between the hotels, hostels, and the CC companies there are approximately 138,419 rooms available, which equals a maximum capacity of 50,522,935 in a year. ➢ Hotels have 82% of the market shares which corresponds to 12,881,674 overnight stays ➢ Hostels have 7% of the market shares which corresponds to 1,115,468 overnight stays ➢ CC companies together have 11% of the market shares which corresponds to 1,634,288 overnight stays

Key Findings: ➢ The market of the Danish accommodation industry as a whole has grown, through the new market creation from the CC companies, leading to overall market share loss of the traditional hotels and hostels. ➢ Suggestions for traditional players to regain market shares include: ○ Use technology to allow for user participation in media creation and sharing, higher use of popular social networking platforms and offering availability through responsive websites and smartphone apps, all to enhance the guest experience and strengthen relationship between customer and company. ○ Offer a more authentic travel experience that allows for the feeling of being local and experiencing the culture of the area and country. ○ A heightened focus on millennials in general and business travellers of this generation, as they are also beginning to choose the CC accommodation offers.

CHAPTER 5. CONCLUSION This report studied the phenomenon of CC as a case study, focusing on the accommodation industry in Denmark (hotels, hostels, and CC companies). The purpose of the study was to better understand the trend, identify the attributes that provide more customer value, and determine the dynamics within the Danish accommodation industry. The research and analysis were guided by specific theories and methodological choices, which lead to answering the main research question: â&#x20AC;&#x153;What is the perceived value of peer-to-peer collaborative consumption from the consumersâ&#x20AC;&#x2122; perspective and how can traditional players in the Danish accommodation industry take advantage of it and regain market share?â&#x20AC;?.

Figure 30 - Conclusion Framework (Own model, 2014) The theoretical framework (p. 7) was useful in guiding the research and analysis on the concepts that needed to be discussed, namely identifying the exact characteristics of CC for the convergence culture analysis, or the attributes of the trend that were discussed in the diffusion of innovations analysis. 81

Moreover, the Theory of Disruptive Innovation focused the research on the data that needed to be collected (e.g. overnight stays, accommodation capacity, etc.), offering the possibility to estimate and determine the market shares of each accommodation provider category, which further allowed for identifying the characteristics of the industry disruption. Equally important, the methodological choices focused the research on gathering data on CC background information, adopter features and perceived values, number of CC companies and the growth of these, accommodation capacity, and overnight stays. The findings revealed that CC could be described having the theory of Convergence Culture as basis, where the major concepts are useful in determining what is happening and why the trend is evolving as it is. The collective intelligence concept of individuals coming together and sharing their knowledge explains the shift in the consumer behavior toward a participatory culture, where they express the will to recreate the traditional communities and control their media world. These actions merge into media convergence, and the analysis focused on determining which media technologies are used by the accommodation providers in Denmark. The analysis showed that CC companies are better at making use of media technologies, as illustrated below in figure 31. Thus they have an advantage over the traditional accommodation providers, as they have built stronger consumer relationships. The analysis of diffusion of innovations revealed that the knowledge about CC spreads through mass media and interpersonal communication channels, although the latter shows much more impact in spreading the P2P CC model. The CC attributes that are most valued by consumers are low costs, convenience, more authentic travel experiences, and creation of trust through the coming together of strangers. Concerning the CC adoption, the analysis showed that CC has reached critical mass in Denmark, with the number of members growing with approximately 3,997 every month and overnight stays reaching 500,000 for Airbnb and 130,000 for HomeExchange. The rate of adoption is growing at a very high rate, especially for Airbnb that have a growth rate of 95% YoY and would thus saturate the market around year 2022 if this growth continues. Finally, the findings from the disruptive innovation analysis showed that CC companies have introduced a new business model based on P2P technology, having new value propositions and attracting in particular the millennials. This has expanded the market of the Danish accommodation industry through new market creation and it lead to market disruption and market share losses for the hotels and hostels in Denmark. However, the data shows that, at least at this point, the disruption has not created a displacement of the market leaders with the CC companies; just like lower-tier hotels

disruption have not dethroned hotels, as Christensen concludes is usually the case. In reality, from what has been observed at the point of this study, they have reached a coexistence phase.

Figure 31 - Summary of Key Numbers (Own model, 2014) Thus the CC companies have gained a lot of traction within very few years by having a technological platform that embraces the users and allows them to participate on their own terms. In comparison it has taken the hotels and hostels decades to gain the same traction and they are still lagging behind in terms of technological application and allowing bottom-up consumer participation. The novelty of applying the combination of the three theories on the accommodation industry in Denmark, along with studying CC from a technological media convergence perspective offered unique findings that could further generate a set of practical suggestions for the traditional accommodation providers. Furthermore this approach of suggestions is a novel solution as opposed to the typical approaches seen in many industries dealing with CC including buying up the competitors or even ignoring them. Thus these suggestions to regain some of the market include use of technology and social networking platforms, offering a more authentic travel experience, and focusing their marketing strategies on the millennial segment and business travellers, which have shown interest for the CC companies. These suggestions can represent the basis for further research as a business case for the hotels, with the purpose to test and identify the return of investment for the set of suggestions. 83

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APPENDICES

Appendix I - Airbnb Email Correspondence

Appendix II - Estimation of Total Amount of Overnight Stays for CC companies

Â 94

Appendix III - Hostel Room Capacity

Appendix IV - Number and Capacity in the Danish Accommodation Industry

Appendix V - Media Technologies in CC Companies

Â 99

100

101

102

Appendix VI - Media Technologies in Traditional Accommodation Companies

103

104

105

106

Appendix VII - Cost Saving Comparison Chart

107

Appendix VIII - Growth in Amount of CC Companies in Denmark

Appendix IX - Growth of CC Users by Available Rooms in Denmark

108

Appendix X - Growth of CC Members in Denmark

Appendix XI - CC Growth by Overnight Stays in Denmark

109

Appendix XII - Calculating the Rate of Adoption Year

Growth by

Percentages of

mount of

adopters

Comments

listings 2010

Calculations are based on a growth rate of 95% YoY.

2011

2012

500

2013

4,200

2014

13,403

2015

26,135.85

2016

50,964.1

2017

99,379.9

2018

193,790.805

2019

377,892.065

2020

736,889.465

2021

1,436,934.395

2022

1,921,500

70%

2,196,000

80%

2,470,500

90%

2,745,000

100%

Airbnb listings in DK in 2014

110

Appendix XIII - Total Amount of Overnight Stays at Hotels and Hostels in Denmark

111

Appendix XIV - Calculating the Market Disruption

Â 112

Appendix XV - Accommodation Industry Overnight Stays in 2012

Â 113