The aim of the presented work is to determine common issues of modern concepts of the sharing economy that can be effectively solved through Blockchain applications. Furthermore, a practical framework is provided that addresses the key factors of implementing Blockchain technology in sharing economy concepts.
The very essence of the sharing economy pertains to old market principles that are coupled with new interpretations, dimensions, and potential. Driven by socio-economic factors, it revolves around a) conscious consumption in a decentralised manner, b) accessibility over ownership, and c) extraordinary efficiency. Thus, it mirrors a new “zeitgeist” which is dawning in various parts of the world. Since technology is a key enabler of sharing economy concepts, Blockchain stands out as a disintermediating and disruptive technology. The hype among information technology enthusiasts, financial investors and traders brings back memories of the dot-com bubble. One important lesson learned from this was the urgent need to distil viable, beneficial and future-oriented business models.
Table of Contents
Chapter 1: Introduction
Chapter 2: Literature Review
2.1 Rationale
2.2 The Sharing Economy: Basic Framework
2.2.1 Principles
2.2.2 Players
2.2.3 Concepts and Drivers
2.2.4 Enablers
2.2.5 Further Issues and Challenges
2.3 Blockchain
2.3.1 What is a Blockchain?
2.3.2 Smart Contracts
2.3.3 Value for Business
2.3.4 Blockchain Issues
2.4 Blockchain and the Sharing Economy
2.4.1 True Decentralisation
2.4.2 Disrupting the Disruptors
2.4.3 New Models
2.5 Full Framework: Blockchain Implementation in the Sharing Economy
Chapter 3: A Justification of the Research Methods Used
3.1 Research Aims
3.2 Research Philosophy
3.3 Research Design and Strategy
3.3.1 Methodology
3.3.2 Data Collection Methods and Sampling
3.3.3 Questionnaire Design
3.5 Data Analysis
3.6 Reliability and Validity
Chapter 4: Results
4.1 Sample and Attitudes
4.2 Drivers
4.3 Enablers and Players
4.4 Challenges and Bottlenecks
4.5 Further Analysis
4.5.1 Differences among Age Groups
4.5.2 Differences among Continents and Professions
5. Discussion
5.1 Introduction
5.2 Interpretation of Results
5.2.1 Sample and Attitudes
5.2.2 Drivers
5.2.3 Enablers and Players
5.2.4 Challenges and Bottlenecks
5.3 Implications
5.4 Limitations
6 Future Work
7 Conclusion
8 References
Abstract
Chain Reactions: Investigating the Impact of Blockchain on the Sharing Economy.
The very essence of the sharing economy pertains to old market principles that are coupled with new interpretations, dimensions, and potential. Driven by socio-economic factors, it revolves around a) conscious consumption in a decentralised manner, b) accessibility over ownership, and c) extraordinary efficiency. Thus, it mirrors a new “zeitgeist” which is dawning in various parts of the world. Since technology is a key enabler of sharing economy concepts, Blockchain stands out as a disintermediating and disruptive technology. The hype among information technology enthusiasts, financial investors and traders brings back memories of the dot-com bubble. One important lesson learned from this was the urgent need to distil viable, beneficial and future-oriented business models. The aim of the presented work is to determine common issues of modern concepts of the sharing economy that can be effectively solved through Blockchain applications. Furthermore, a practical framework is provided that addresses the key factors of implementing Blockchain technology in sharing economy concepts.
List of Figures
Figure 1: Funding by Company (in billion US$)
Figure 2: Overview Research Logic
Figure 3: Relevance of Blockchain within Sharing Economy Papers
Figure 4: Relevance of Sharing Economy within Blockchain-related Papers
Figure 5: CLR Result, Sharing Economy: Publications Per Year
Figure 6: CLR Result, Blockchain: Publications Per Year
Figure 7: Honeycomb, Version 3
Figure 8: Categories of Players (First Part of the Framework)
Figure 9: Categories of Social Drivers (Second Part of the Framework)
Figure 10: Enablers (Third Part of the Framework)
Figure 11: Basic Framework of Factors Associated With Sharing Economy
Figure 12: What is a Blockchain?
Figure 13: Hexagon of Honeycomb Including Blockchain-Related Projects
Figure 14: The Dapp Kings: “Distributed Business Entities”
Figure 15: Complete Framework derived from the Reviewed Literature
Figure 16: Overview: Research Methodology
Figure 17: Sample Locations (Continents, European Countries)
Figure 18: Sample Age
Figure 19: Sample Highest Qualification
Figure 20: Familiarity with Blockchain and Sharing Economy
Figure 21: Participation in Sharing Economy
Figure 22: Likelihood of Blockchain Implementation into Sharing Economy
Figure 23: Will Blockchain Transform Sharing Economy?
Figure 24: When will Blockchain Transform Sharing Economy?
Figure 25: Should Blockchain Technology be regulated?
Figure 26: Social Drivers (Scores)
Figure 27: General Economic Drivers (Scores)
Figure 28: Economic Drivers - Supply Side (Scores)
Figure 29: Economic Drivers - Demand Side (Scores)
Figure 30: Technological Drivers (Scores)
Figure 31: Comparison and Overview of Drivers (Scores)
Figure 32: Average Rankings: Enablers (Scores and “Other”)
Figure 33: Average Rankings: Players (Scores and “Other”)
Figure 34: Relevant Industries from Open Questions (Coded and Structured)
Figure 35: Average Rankings: Consumers (Scores and “Other”)
Figure 36: Average Rankings: Businesses (Scores and “Other”)
Figure 37: Average Rankings: Institutions (Scores and “Other”)
Figure 38: Average Rankings: Challenges (Scores and “Other”)
Figure 39: Bottle Necks and Solutions from Open Questions (Coded and Structured)
Figure 40: Social Driver: Safety of Consumers (Answers According to Age Groups)
Figure 41: Economic Driver (Supply): Deregulation of Transactions (Answers According to Age Groups)
Figure 42: Likelihood of Blockchain Implementation in Sharing Economy (Answers According to Continents)
Figure 43: Technological Driver: Scalability (Mass Adoption) (Answers According to Professions)
Figure 44: Adjusted Framework of Key Factors Affecting the Implementation of Blockchain Technology into Sharing Economy
List of Tables
Table 1: Reduction of Transaction Costs in the Sharing Economy
Table 2: Many Faces of Trust in Sharing Economy
Table 3: Overview of Players
Table 4: Overview of Social Drivers
Table 5: Overview of Economic Drivers
Table 6: Overview of Technological Drivers
Table 7: Overview of Enablers and Challenges/Issues
Table 8: Question Block 1: Segmentation and General Attitude
Table 9: Question Block 1: Challenges and Likelihood
Table 10: Question Block 2: Drivers
Table 11: Question Block 2: Enablers and Players
Table 12: Sample Professions
Abbreviations
Abbildung in dieser Leseprobe nicht enthalten
Chapter 1: Introduction
“I've been working on a new electronic cash system that's fully peer-to-peer,
with no trusted third party.”
(Nakamoto, 2008a).
In 2008, an unknown person or group of persons, under the pseudonym Satoshi Nakamoto, introduced the concept of the first Blockchain. Four years earlier, in 2004, social sharing and social exchange of value was already permeating the very core of most advanced economies. In particular “[…] information, culture, education, computation, and communications sectors” have been playing critical roles as they constitute main drivers and enablers of the aforementioned trend towards social sharing and exchange (Benkler, 2004, p.278). More specifically, Benkler describes information technology as a key enabler of such measurably effective sharing practices. He refers to the extensive availability of software and distributed computing which, in combination with easily accessible wireless networks, ultimately allow such large-scale effects on socio-economic behaviour. The underlying reason for this development is “[…] the highly distributed capital structure of contemporary communications and computation systems […]” (Benkler, 2004, p.278). In other words, the lower the capital costs required for individuals who want to engage in economic activities, the stronger the tendency towards decentralised systems based on social relations in comparison with hierarchies and existing markets.
In order to put the dimensions of the sharing economy into perspective, Zobrist and Grampp (2015, p.3) calculated a total of $ 12 billion which has been invested in sharing economy start-ups. As a matter of fact, investments in the sharing economy are higher than the amounts invested in social networks such as Facebook and Twitter (figure 1).
Figure 1: Funding by Company (in billion US$)
Abbildung in dieser Leseprobe nicht enthalten
Source: Zobrist and Grampp 2015, p.4
In the United Kingdom, the sharing economy is expected to expand over 30% per year within the next ten years and generate £ 18 billion revenue for the companies that run sharing economy platforms (PwC, 2016). Moreover, about £ 140 billion worth of transactions per annum are predicted for 2025.
Despite of the relatively large investment sums and growing revenues, the reviewed literature suggest that we do not live in a moment of history that humanistic sharing is unique to. However, the following observation adds another perspective to the traditional notion of sharing. If a society has access to certain technologies that enable agents to individually control effective creation and exchange of value, it can enhance modalities within social, markets and production (Benkler, 2004). However, the extent to which a society is ready to engage in sharing tangible assets like cars and space or intangible assets like time and skills is not determined by technology. In fact, it functions as an enabler rather than an actual driver of such developments. According to Killeen (2016), three major movements are occurring within recent years that have a particular complementarity. The first two of which are particularly relevant for this work. First, a decentralised ledger technology, called Blockchain, which forms the basis for applications such as crypto currencies of which Bitcoin is the most popular at the current time. Second, the sharing economy which can be defined as a peer-to-peer market system that enables efficient collaborative consumption and access to underutilised assets via a platform-based online coordination of supply and demand. Although the third movement, Internet of Things (IoT), is of a comparable importance and relevance to society and potentially even sharing economy concepts, it is not within the specific scope of this work.
The combination of the sharing economy and the Blockchain technology can be seen as a setup that creates a new field that is gradually getting attention in economy and research. What Blockchain and the sharing economy have in common on a high level, is the peer-to-peer connectivity. Recent research within the intersection of these spheres reveals possible combinations of socio-economic drivers, enablers and key players that could lead to major disruptions in many industries within the coming years (Avital et al., 2016: Huckle et al., 2016; Killeen, 2016; Lundy, 2016; Sundararajan, 2016; Pazaitis De Filippi and Kostaki, 2017; De Riviera et al., 2017). Tapscott and Tapscott (2017, p.4) describe the Blockchain technology, in comparison with the Internet, as “[…] distributed, not centralized; open, not hidden; inclusive, not exclusive; immutable, not alterable; and secure.”
In other words, this new technology allows entire societies to create and exchange value in an unprecedented way. The reason for that is one of the most outstanding use cases of Blockchains – transferring value over the Internet as easily as sending an email, but in a decentralized way and “[…] with no central server or trusted parties, because everything is based on crypto proof instead of trust” (Nakamoto, 2009). From these properties, Wood (2016) derives four high-level implications which are also relevant for the sharing economy:
- “Blockchain solves the issue of multiparty contention without having to involve a human
- Trust is no longer needed to contentiously interact with a third-party.
- This is the first ever instance of a technology which can do such a thing
- Practically speaking, we have just commoditi[s]ed the rarest and most delicate of all intangible assets: trust”
In order to put the impact of these implications into a more practical context, “[t]hink about gambling without a casino, think about stock trading without an exchange, think about real estate transactions without deeds, and think about transactions without clearing houses – that is the world we are heading into. We have just barely scratched the surface today” (Sundararajan, 2016, p.85). According to the literature, opportunities seem vast and might reach far across various industries having a great impact on economic activities such as manufacturing, trade, auditing and accounting services by making them more efficient and cheaper. However, the opportunities do also including activities within large societies that couldn’t be monetised yet (Avital et al., 2016; Lundy, 2016; Botsman and Rogers, 2010). Lundy (2016) suggests that the short-term impact and long-lasting effects of Blockchain will allow entire industries to be transformed. He supports “[t]he vision that blockchain will deliver […] nothing less than the reshaping of society and the economy” (Lundy 2016, p.3). As a result, an overwhelming emergence of new businesses leads to an increasing uncertainty about the question, which business models meet the prerequisites in order to prevail throughout the development of the sharing economy. For instance, such models would require a reasonable and realistic relationship between added value and congruency with socio-economic and technological trends.
What Blockchain and the sharing economy have in common on the most general level, is peer-to-peer (P2P) connectivity. Blockchain, as a peer-to-peer transaction infrastructure has a growing importance for marketplaces (Killeen, 2016, pp.485-486). Avital et al. (2016, p.2) refers to it as an ecosystem that enables novel types of organisation and cooperation between humans. Moreover, he specifies that “[…] blockchain might allow new heights of liberty, equality, and fraternity” which matches the empowerment of the consumer according to sharing economy concepts. Using services such as eBay, Uber and Airbnb allows individuals to connect with each other (Uber, 2017, Airbnb, 2017). However, Blockchain applications enable people to not only connect, but also share and transact in a direct manner which introduces the notion of a real sharing economy.
Problem
A lot of effort is currently being invested in categorising and segmenting individual innovations, concepts and business models that arise from both phenomena, the sharing economy and Blockchain technology. Despite the high growth rate of these two industries separated from each other, an increasing amount of business models in the intersection of the sharing economy and Blockchain are also being introduced rapidly. In this context, the quantity of new businesses might indeed indicate a certain value from sharing economy models which are likely to employ Blockchain technology in any way.
However, the current literature offers only highly theoretical concepts about socio-economic drivers that are involved in combining Blockchain technology with the sharing economy. Moreover, the similar underlying psychology of both phenomena as well as their shared cultural impetus represent a certain confluence in terms of time and nature (Killeen, 2016; Sundararajan, 2016; Lundy, 2016). Accordingly, the conceivable interconnectivity of Blockchain and the sharing economy is likely to be subject to common factors that will ultimately drive their broad adoption. There is a lack of research dedicated to a more practical perspective on the underlying key factors within the intersection of the sharing economy and Blockchain.
In addition to the highly theoretical perspective on the topic, the great number of emerging business ideas in a virtually unexplored ecosystem might remind one of the dot-com bubble. Given the increasingly high volume of investments done by a great number of individual investors with potentially little to no technical understanding, might indicate distinct parallels between the proliferation of Blockchain technology and the tech bubble in the late 90’s (Iansity and Lakhani, 2017; Ovide, 2017; Coinmarketcap.com, 2017). A key lesson from the actual dot-com bubble was that the start-ups and projects themselves were not responsible for neither the formation of the bubble nor the burst. The rise and collapse of their share prices had no significant correlation with neither the actual economic potential, nor the quality of their management. The reason lies in the capital markets which channelled money into the new business sector, but without the technical, financial and commercial due diligence on the side of investors, that ought to be involved in evaluating the projects, businesses and their prospective value (Mills, 2001; Iansity and Lakhani, 2017).
Current approaches to classification and typology around sharing economy concepts together with potentially suitable Blockchain applications have comparable weaknesses. Similarly to the dot-coms, such specific sharing economy concepts are built on new business models, rather than on proprietary technologies, traditional financial measures or conventional approaches to business (Mills, 2001). Moreover, sharing economy concepts that include Blockchain technology, are probably going to a) entail entirely novel customer value propositions, b) appeal to different customer groups and c) form the base for novel supply chain systems Grinevich and Huber (2016, pp.3-4).
Ultimately, there is little to no chance to prevent a bubble from forming in the Blockchain and crypto currency ecosystem – if it is not already in the process of forming. What appears more likely, however, is to obtain and achieve more clarity in order to evaluate and distinguish particularly promising sharing economy concepts which are likely to benefit from specific Blockchain applications and thus, bring value to society. Therefore, the role of the established sharing economy platforms needs to be analysed along with the importance of other players in comparison with the companies behind the respective platforms. A certain problem, derived from the literature, had a strong influence on this work and can be formulated as a question: How can the peer-to-peer market system be further improved and in what way could Blockchain technology be employed for that, given its disintermediating and disruptive potential? (Avital et al., 2016; Huckle et al., 2016, Killeen, 2016; Lundy, 2016; Sundararajan, 2016; Pazaitis, De Filippi and Kostakis, 2017; De Riviera et al., 2017).
Research Question and Objectives
The object of the work are sharing economies and Blockchains, and the main research question concerned is: how can Blockchains improve the sharing economy? The main motivation of this work is, therefore, to explore the transformation of economies given the movement of social sharing and exchange as well as the development of a novel and potentially disruptive information technology. The focus lies on key factors such as drivers, enablers and players in relation to the wider logic that determines the application of Blockchain in sharing economy concepts.
Although there might be no remedy against disruption, hype and speculation, there is a need for a reliable and hence more practically-oriented evaluation of key factors in order to identify fundamental aspects of a promising Blockchain implementation in the sharing economy. More specifically, a comprehensive analysis of drivers, enablers and players along with a survey of technical experts might provide a more reliable view of the feasibility and suitability of implementing Blockchain technology in the sharing economy. In other words, which are the drivers, enablers and players that are not only closely associated with the sharing economy, but also refer to business models that may employ the Blockchain technology in a highly beneficial manner.
The individual objectives that are required in order to approach the before mentioned practically-oriented question begins with, firstly, an orientation within the literature. In this process, the main focus lies on the definition of the sharing economy, a distinction between relevant concepts and the respective role of technology and innovation.
Secondly, we require an analysis of the principal issues affecting the relevant sharing economy concepts as well as the potential impact of Blockchain technology on the above mentioned issues.
Thirdly, this will allow to extract key drivers, enablers and players of Blockchain implementation in sharing economies. The results from the literature review constitute the base of an expert survey of the technical Blockchain community. Subsequently, the outcomes of the data analysis are used to a) validate the literature review results, b) discover new insight and c) triangulate the results with respect of distinguishing characteristics among the respondents. The final objective is to create a framework for blockchain implementation in the sharing economy that confirms or challenge findings from the literature and provides guidance for evaluating sharing economy concepts that are suitable to implement Blockchain technology.
Potential Impact and Dissertation Structure
The before mentioned objectives are, eventually, supposed to shed more light on how business models and strategies in the sphere of Blockchain-enabled sharing economy might be evaluated in a more reliable manner. This is enabled thorough an analysis of the confluence and common grounds of both developments on which novel business models are built upon. Compared to approaching each segment individually, research and practitioners can achieve a closer and interconnected perspective on the combination of Blockchain and the sharing economy.
We strive to create a framework, which contributes to the academic community by providing guidance that is based on literature and evidence from data analysis. In order to do so, we primarily review the literature of both spheres, the sharing economy and Blockchain technology (section 2.2 and section 2.3) as well as the intersection between them (section 2.4). Then, we extract relevant drivers, enablers and players associated with the implementation of Blockchain technology into sharing economy concepts. As a next step, we decided to survey Blockchain experts from different professional disciplines in order to add their opinions about specific factors as a layer of practically oriented expertise to the intersection between both subject areas, the sharing economy and Blockchain technology. For the purpose of the survey, we created a questionnaire based on the factors from the framework along with additional elements in order to acquire a deeper understanding and further insights. Subsequently, we analyse and discuss the results of our data collection in order to adjust the framework in accordance with the literature and the experts’ opinions. Finally, we draw implications from our findings in order to answer the research question (figure 2).
Research Question:
How can Blockchain Technology improve the Sharing Economy and which key factors are involved?
Objectives
1. Identify, analyse and structure the principal factors affecting the sharing economy and in particular the role of technology and trust.
2. Explain the potential impact of Blockchain technology on sharing economies and extract implementation critical success factors
3. Determine key drivers, enablers and players of Blockchain implementation in sharing economies.
4. Incorporate the experts views and key factors into the framework and discuss potential implications
Figure 2: Overview Research Logic
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
Chapter 2: Literature Review
2.1 Rationale
In order to determine concepts of the sharing economy that are relevant for this work, along with key characteristics, attributes and other factors, a literature review is conducted and presented in this chapter. The approach to identify appropriate and relevant literature included, besides traditional literature analysis, an analytical tool called “computational literature review (CLR) (Mortenson and Vidgen, 2016). This tool was used to processes, compare, and evaluate large numbers of abstracts from academic papers along with similar resources. The outputs include both, metric and visual presentation of results which can a) highlight hitherto undetected authors and resources, b) contribute to the overall orientation within the literature, and c) provide useful insights through metadata and clustering of content.
In the context of this work, the outputs of several iterations of processing various inputs contributed to supplement the reviewed literature by suggesting additional papers as well as indicated that Blockchain and the sharing economy might, indeed, be intrinsically interconnected. The following two figures show two respective topic clusters from an analysis of i) 3244 sources associated with the sharing economy (Figure 3) and ii) 451 sources associated with Blockchain (Figure 4).
Figure 3: Relevance of Blockchain within Sharing Economy Papers
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
Figure 4: Relevance of Sharing Economy within Blockchain-related Papers
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
While the topic cloud from sharing economy sources (Figure 3) indicates a strong focus on information systems and technology. The Blockchain topic cloud (Figure 4) shows a much clearer indication that collaborative economy and related topics are interconnected and, thus, relevant. Two further outputs of the CLR provide information about the years in which the same sets of papers have been published.
Figure 5: CLR Result, Sharing Economy: Publications Per Year
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
Figure 6: CLR Result, Blockchain: Publications Per Year
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
The outputs of the CLR illustrate the topical nature of both subjects by showing a surge in published papers and similar sources associated with either the sharing economy or Blockchain technology (figures 5 and 6). However, almost the entire body of literature used for the purposes of this work can be considered recent since the chosen sources are not older than three to four years except for a few individual sources. Within the following section, a basic notion of the sharing economy is extracted from the literature along with approaches to categorising myriad examples of sharing economy concepts.
2.2 The Sharing Economy: Basic Framework
2.2.1 Principles
In principle, sharing of resources is nothing new at all. Renting or leasing of resources is a worldwide spread practice which has been around for decades. However, the proliferation of the internet enables a) short-period and b) small-scale sharing of resources in an easy and profitable manner (Haucap, 2015). Hamari, Sjöklint and Ukkonen (2015, pp.2047-2048) describe the sharing economy as “[…] an emerging economic-technological phenomenon that is fuelled by developments in information and communications technology (ICT) […]”. Moreover, there is a consensus within the literature that the term sharing economy is an umbrella concept of an economic system with a growing number of consumers. According to Zobrist and Grampp (2015), sharing economy concepts are disrupting various traditional business sectors and in particular hotels, workforce and transport. They describe the largely market-based concept, in its simplest form, as the process of renting out underutilised assets. Moreover, the direct contact between supplier and customers is paramount and typically coordinated via online platforms. More specifically, Hamari, Sjöklint and Ukkonen (2015, p.2047) define the sharing economy as “[t]he peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services.”
In fact, the term is associated with several synonyms such as “collaborative consumption” “crowd-based capitalism” and “access economy” (Botsman and Rogers, 2010; Sundararajan, 2016; Eckhardt and Bardhi, 2015), of which the latter two, specifically, refer to the striking misuse of the term ‘sharing’. Eckhardt and Bardhi (2015) deny the notion of sharing within such market concepts, entirely, by reinforcing that “[s]haring is a form of social exchange that takes place among people known to each other, without any profit.” This perspective is in accordance with Sundararajan (2016, p.27) who underlines the mainly commercially oriented exchanges that take place within such communities. However, the literature suggests that the sharing economy revolves around what Dervojeda et al. (2013, p.3) describes as “[…] a transition from ownership towards accessibility […] across a wide variety of markets.” In these systems, the consumer pays the supplier for temporarily granted access-rights to a product or a peer-to-peer service. This way of conducting business per se, is certainly neither new nor innovative as, for instance, traditional B2C car rentals or B2B outsourcing concepts demonstrate (Dervojeda et al., 2013, p.3). However, there is agreement that, as far as technological advancements are concerned, not only conventional business models are subject to change, but also entire industries may be disrupted as the implementation of certain technologies in the sharing economy continue (Grinevich and Huber, 2016; Hamari, Sjöklint and Ukkonen, 2015; Eckhardt and Bardhi, 2015; Sundararajan, 2016; Dervojeda et al., 2013; Botsman and Rogers, 2010).
In order to illustrate the expansion of the sharing economy throughout 16 industries and 41 subcategories, the third version of the “Honeycomb” by Owyang (2016) is shown in figure 7. Older versions that demonstrate the fast development of the sharing economy and its proliferation throughout different industries can be found in appendix A. While the first version of the “Honeycomb” in May 2014 only showed six industries (goods, food, services, transportation, space, and money) and 14 subcategories (inner circle of version 3), the second version which was published only seven months later listed already twelve industries including 30 subcategories.
Figure 7: Honeycomb, Version 3
Abbildung in dieser Leseprobe nicht enthalten
Source: Owyang, 2016
To shed more light on the efforts which have been done in order to categorise and structure the activities associated with the sharing economy along with the impact on society, three further frameworks and schematic diagrams have been compared. Those frameworks are a) Gansky’s Meshy-ness Grid which allows a categorisation of the products involved in the broader concept of sharing and b) Botsman’s Four Quadrants – a framework that allows to organise collaborative consumption models according to four domains of activities: production, consumption, finance, and education (Sundararajan, 2016, p.79-82). The third model c) is a framework which revolves around the mapping of effects that an established peer-to-peer sharing economy platform has on values of a society (Westerbeek et al., 2016, p.226).
In fact, those frameworks complement each other well with regard to sharing, for instance, underutilised assets. They allow to evaluate a sharing concept by a) categorise the object (asset) which may be shared, b) provide guidance for behaviour and activities involved in sharing, and c) allow insights about the effects on values in society. Since the sharing economy is a complex market structure and involves certain socio-economic factors, such frameworks enable researchers and professionals to explore and analyse different use cases in a systematic manner.
As it can be seen in the previous sections, definitions of the term along with a segmentation of the manifold use- and business cases of the sharing economy give an overview of the broad notion of the basic economic system. Except for the mapping framework of Westerbeek et al. (2016), these are rather descriptive approaches of existing sharing economy concepts with little to no explanatory potential for the future of the sharing economy. The literature provides a basic notion of the sharing economy which revolves around coordinating multiparty transactions regarding either services or access rights to assets in exchange for money. Thus, appears reasonable to distinguish between the interconnected parties as a) consumers, b) businesses (or platforms) and c) Institutions (Sundarajan, 2016; Haucap, 2015; Evans and Schmalensee, 2016; Stephany, 2015; Botsmann and Rogers, 2010; Vinod Kumar and Dahiya, 2017).
In summary, the sharing economy is a complex and dynamic market structure which includes consumers and businesses who are coordinated via online platforms and driven by socio-economic factors. Those factors along with specific technological aspects of implementing Blockchains into sharing economies as well as the potentially beneficial impact remained yet to be tested in this particular context. Drivers, enablers, and players were deduced from the sharing economy literature since it is the core subject which could benefit from improvements enabled by potentially disruptive technologies such as Blockchain – comparable to the internet-induced advancements of successful sharing economy concepts such as Uber and Airbnb.
2.2.2 Players
Consumers
In a retrospective view on the economic activities throughout human history, Sundarajan (2016, p.4-5) suggests that mass production and mass distribution have led to a worldwide economy which is dominated by large corporations. But with regard to individual consumers, sharing of resources is not a novel concept and neither are the forms of exchange, commerce and employment associated with the sharing economy (Sundararajan, 2016, p.5). Shared flats or car-sharing, for instance, are long-existing examples that are based on the common idea to divide and distribute fix costs by sharing the respective resources. Just like libraries and video stores, such concepts were subject to manageable competition (Haucap, 2015).
However, this competition between such companies is changing ever since the ongoing digitisation enables technological capabilities which result in the emergence of consumer-driven sharing economy models (Evans and Schmalensee, 2016; Haucap, 2015; Stephany, 2015; Sundararajan, 2016; Botsmann and Rogers, 2010). In other words, “[t]oday’s digital technologies seem to be taking us back to familiar sharing behavio[u]rs, self-employment, and forms of community-based exchange that existed in the past” (Sundararajan, 2016, p.5). In addition to that, such technology-powered markets effectively enable and encourage entrepreneurial behaviour to such an extent, that industries which used to be dominated by corporations are being disrupted (Kumar and Dahiya, 2017; Sundararajan, 2016). Furthermore, the utilisation of technology allow such seemingly traditional forms of economic activities to extend beyond the traditional notion of economic community consisting of family, friends and neighbours (Sundararajan, 2016; p.5-6).
Communities
With regard to the aforementioned empowerment of individual consumers, the associated economic community is described by Sundararajan (2016, p.5) as “[…] digitally vetted subset of the population […]”. Botsman and Rogers (2010, p.41-56) go one step further by introducing the notion of such a community as people who distrust corporations and thus, are keen to change to alternatives. However, both views on communities are consistent with each other by referring to a collective of consumers.
Furthermore, the major reasons behind the emergence of various alternatives to services and products provided by large corporations are as follows: first, a substantial cost reduction of searching via the internet. In other words, the effective way of matching supply and demand among individuals through online platforms. In particular, matches of supply and demand that are associated with small transactions such as overnight stays and car rides (Haucap, 2015). Second, certain capabilities that allow to partially solve the problems due to the lack of trust between the usually unfamiliar participants of such transactions (Sundararajan 2016, p.6; Haucap, 2015, p.3).
Businesses and Platforms
At this point it is important to distinguish between Businesses as one of the three key players of the sharing economy (consumers, businesses and institutions) and businesses in the role of consumers. The latter of which, relates to another example for traditional sharing of resources among businesses. Comparable to the individual consumers, B2B sharing is becoming more elaborate and efficient due to the advancements of information and communication technology (Haucap, 2015).
Businesses as players of the sharing economy (Platforms)
There is a certain lack of consensus within the literature about the role of businesses such as Uber, Airbnb and TaskRabbit. Although, they are repeatedly mentioned as examples for the sharing economy, these organisations primarily operate online platforms which merely enable and facilitate transactions by aggregating supply and demand and matching them accordingly. In order to do so, the range of services and activities performed by such companies comprise, among others, marketing (brand), consultancy (user support), and centralised trust (reputation of users and transactions between users). However, the core services of these market-systems, thus the actual value, is created and exchanged among the consumers. In this context, Sundararajan (2016, p.77) proposes a description “[…] of Uber and Airbnb as simply giant ‘micro-outsourcing’ operations, within hundreds of thousands, and maybe soon, millions of small providers.”
A comparison between traditional sharing and the sharing economy can be seen in the following table 1. It shows the respective activities of the old and new approach to peer-to-peer car sharing and indicates the resulting reduction of transaction costs. It illustrates the extent to which platforms enable the sharing economy by facilitating search, bilateral decisions, and policies.
Table 1: Reduction of Transaction Costs in the Sharing Economy
Abbildung in dieser Leseprobe nicht enthalten
Source: Demary, 2015, p.8
According to Evans and Schmalensee (2016), such matchmakers have, unlike traditional businesses, a consistently smaller proportion of fixed capital. Instead, they utilise one group of consumers as a source of access to assets which is, subsequently, matched and sold to another group of consumers. In contrast to the evident matchmaking activities of Uber and Airbnb, Evans and Schmalensee (2016, p.2-3) also mention Apple, Google, and Microsoft who are reportedly utilising this profitable concept by matching, for instance, developers and users. Despite apparent advantages, there is a growing criticism and an increasingly critical view of matchmaking businesses and platforms in the sharing economy. Bradley and Pargman (2017) highlight the threat of an increasing social homophily due to competition and distrust among consumers along with precarious employment situations and ultimately an even more unequal concentration of capital and power. In addition, monopolies within respective niches could occur which, in theory, allow companies such as Uber and Airbnb to impose exploitative conditions and constraints to a vast number of consumer groups.
In fact, most matchmakers provide a more beneficial and “[…] elaborate governance system of laws, enforcement, and penalties to keep their participants in line” (Evans and Schmalensee 2016, p.4).
Institutions
Governments, NGOs and educational institutions can also take part in sharing economies as consumers. These and other institutions can engage in either consuming or supplying idle resources or use various P2P services associated with sharing economy models (Grinevich and Huber, 2016; McKinsey 2016, p.96). The following institutions and their respective roles regarding the sharing economy and Blockchain are considered a key player position.
Governments can take part in the sharing economy at different levels, including at local, regional, and national levels as well as international settings. Moreover, legislation and regulation regarding labour, infrastructure as well as specific rules on city-level may substantially influence sharing economy models (Grinevich and Huber, 2016). The OECD (2017) emphasises particular challenges in effectively addressing opportunities as well as in stimulating innovation, expansion and development of both, traditional sectors and the respective sharing economy concepts.
International Organisations such as the United Nations, the European Union or the OECD may become involved as well since “[t]he rapid growth of the sharing economy is placing pressure on existing policy frameworks.” (OECD, 2017). Furthermore, Grinevich and Huber (2016, p.7) point out that an effective coordination between “[…] policy makers, public sector organisations and other local, regional and national stakeholders is required.” In this context, Demary (2015, p.3) suggests that further proactive regulation might be more appropriate since some sharing economy companies (platforms) act as if the existing rules do not apply to their business models.
Currently, education and research play a secondary role in terms of effectively influencing the development of the sharing economy. However, evaluation, insights and frameworks for various issues of the sharing economy can lead to a better understanding of future developments in certain industries. Moreover, McKinsey (2016, p.96) suggests, that novel types of institutions might emerge as the expansion of sharing economy concepts continues.
The focus of this paper is on commercially-oriented and crowd-based market system that includes three types of players: consumers, businesses, and institutions. This division might not be perfect because, for instance, businesses could act as consumers or individual entrepreneurs might change their activities so that they resemble those of businesses by grouping up with other individuals and dividing commerce related task among each other.
Figure 8: Categories of Players (First Part of the Framework)
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
So far, the literature has provided a general notion of the sharing economy and what groups of players are involved (figure 8). This allowed us to construct the first part of the framework that is going to be further developed from the literature within the following sections. Therefore, the following section first clarifies the differences between the existing categories of sharing economy concepts. Then, it provides an overview of factors that drive actions of the above mentioned players within market systems associated with the sharing economy.
2.2.3 Concepts and Drivers
Pure Sharing Economy vs. Sharing-Like
A further perspective on the term sharing economy by Grinevich and Huber (2016, p.3) includes a distinction between a pure sharing economy and sharing-like concepts. More specifically, they point out a missing consensus throughout the literature about specific characteristics that constitute a sharing economy. First, they refer to a definition by Frenken et al. (2015), according to which a model is qualified as pure sharing economy, if a “[…] temporary, and possibly paid for, access to underutilised physical assets […]” is granted and limited to a consumer-to-consumer (C2C) transaction. However, by putting the commercial aspect of the transaction on a facultative basis, this part of the notion of the sharing economy is inconsistent with those of Sundararajan (2016) and Eckhardt and Bardhi (2015) who consider the commercial orientation an essential element.
Second, and following the premise of a missing consensus within the literature about specific qualifiers of a sharing economy, Grinevich and Huber (2016, p.3) provide a list of four models that they consider sharing-like concepts.
Peer-to-peer marketplaces relate to a particular focus on transferring ownership of assets rather than granting access (i.e. eBay, OpenBazaar, Gumtree).
Product service systems (PSS) in which businesses provide a platform as well as assets that are supposed to be rented by the consumers. Although this model strongly resembles traditional B2C rental businesses it remains a relevant sharing-like concept due to the increasing trend of access over ownership of assets mentioned within the respective sharing economy literature (Grinevich and Huber, 2016; Hamari et al., 2015; Eckhardt and Bardhi, 2015; Sundararajan, 2016, Dervojeda et al., 2013; Botsman and Rogers, 2010).
Business-to-Business (B2B) models which include “[…] sharing, renting, lending and re-selling of underutilised assets […] between organisations rather than individuals and households” (Grinevich and Huber, 2016, p.3). This particular distinction may not be necessarily relevant as the lines between participating consumers, self-employed individuals and businesses could become increasingly blurry in sharing economy concepts.
Access to intangible assets facilitated via marketplaces. Such models are mainly about services since individuals exchange time and skills in a P2P or consumer-to-business manner. Examples are, thus, related to workforce such as TaskRabbit (TaskRabbit, 2017) and Freelancer or services such as Uber.
Thus, the common ground within the respective literature is that the sharing economy can be considered a market-structure which is typically crowd-based, but does not exclude businesses in the roles of consumers or suppliers. In this context, Botsman and Rogers (2010, p.41-56) mention a transition within the mind-set of interconnected communities which they refer to as “from generation me to generation we”. However, the before mentioned integrated role of businesses as well as the consumer focus on access over ownership (Eckhardt and Brandhi, 2015; Sundararajan, 2016) challenge such a shift of a collective attitude towards consumption as a conceptual condition of the sharing economy. In other words, successful business models in the sharing economy do not exclusively require a certain community that is willing to engage in sharing their assets among each other since it does not accurately mirror the expected benefits of the consumers. More specifically, Eckhardt and Brandhi (2015) underline the importance to distinguish between the benefits that comes with having access to a particular asset, compared to disadvantages of owning and or sharing it. They summarise these benefits as “[…] convenient and cost-effective access to valued resources, flexibility, and freedom from the financial, social, and emotional obligations embedded in ownership and sharing.”
As a result, it can be distinguished, between a) collaborative consumption as a decentralised form of sharing economy involving communities of people who exchange access to tangible and intangible assets for money (P2P, C2C) (Botsman and Rogers, 2010, p.41-56) and b) models of an access economy or crowd-based capitalism which are understood as inclusive terms for similar transactions, in an either centralised or decentralised structure which also includes businesses (P2P, C2C, B2C, B2B) (Grinevich and Huber, 2016; Hamari, Sjöklint and Ukkonen, 2015; Eckhardt and Bardhi, 2015; Sundararajan, 2016). Therefore, it can be deduced that three different types of drivers have a strong influence on the activities of the groups of players (section 2.2.2): social and economic drivers as well as technology.
Social Drivers
Hamari, Sjöklint and Ukkonen (2015, p.2047) name two major reasons for increasing popularity of sharing economy concepts within the western world. First, they mention a growing concern about climate change and a subsequently increasing appeal of consumption in a local and communal manner. Second, they describe a tendency towards collaborative consumption among those geographically clustered social groups or communities.
According to several observations mentioned by Sundararajan (2016, p.66), sharing economies have their highest growth rates primarily in urban areas. In this context, he also states that “[c]ities are sharing economies” by referring to accustomed patterns of sharing behaviour such as shared-flats, bus driving and several other public facilities. Moreover, such a dense population and the concomitant geographic collocation offers more possibilities of peer-to-peer exchanges. As a result, Sundararajan (2016, p.66), concludes that city dwellers are “[…] intrinsically better suited to adopt digitally mediated sharing behavio[u]rs.”
Economic Drivers
High unemployment rates and low purchasing power as consequences of the economic crisis in 2009 lead to people seeking for alternative ways to earn and save money. Such constraints increase peoples’ willingness for lending or sharing. For instance, home cooks began to offer their services on dedicated sharing economy platforms such as mealsharing.com. Peer-to-peer money lending became more popular since the effects of the crisis made it significantly more difficult to acquire loans from banks (Dervojeda et al., 2013, p.12).
Although the specific causes and reasons behind the increasing popularity of the sharing economy might differ, the underlying economic drivers remain the same. One of the most obvious is economic gain from effective monetisation of underutilised assets or skills (Evans and Schmalensee, 2016; Haucap, 2015; Stephany, 2015; Sundararajan, 2016; Botsmann and Rogers, 2010). Another important factor associated with economic incentives are the low entry barriers and low capital risks for consumers to participate (Deloitte, 2015, p.12).
Technological Drivers
As already mentioned in section 2.2.2 (Businesses and Platforms), online platforms and applications are considered the core of many sharing economy concepts. In addition to that, the technological capabilities of individual consumers (section 2.2.2 Consumers) support the notion of technology as a main driver of the sharing economy (Sundararajan, 2016; Vinod Kumar and Dahiya, 2017). Usually, the information and communication technology allows companies to create such platforms. In fact, some attempts of sharing resources over a certain period of time used to fail due to high search and transaction costs. These costs, however, have been reduced significantly as the companies as well as the consumers began to utilise the internet (Haucap, 2015, p.1).
In summary, the basic categories of the most impactful drivers regarding the participants or players of sharing economies are certain socio-economic drivers and technological advancements (figure 9). In the following section an overview of the enablers associated with the sharing economy is provided.
Figure 9: Categories of Social Drivers (Second Part of the Framework)
Abbildung in dieser Leseprobe nicht enthalten
Source: Author’s own work
In contrast to drivers, which are understood as strongly influencing factors related to the behaviour of the players, enablers are considered in a more general manner. According to De Rivera et al. (2017), “[s]ectoral classifications, technological functionality, and discursive modes of understanding sharing and collaborative economies all provide valuable insights, but when taken individually important gaps are evident, not least in their inter-system isolation, but most particularly when technology, such as platform architecture and user interfaces, is disassociated from wider social and economic conditions of possibility.”
In other words, the following enablers are referred to as broader factors that might influence developments of the sharing economy rather indirectly.
2.2.4 Enablers
In the context of sharing economy, and according to Clements (2014, p.107), technology creates possibilities which can lead to the development of a culture of collaboration (Gawel, Machur and Pennington, 2016, p.11) enabling and efficient management of urban environment and natural resources (Vinod Kumar and Dahiya, 2017, pp.42-43). Such novel systems require certain regulatory frameworks in order to keep them operating regardless of increased complexity (Dervojeda et al., 2013, p.14) which involves a mutually trusted party and, in most cases, that party is an institution (PwC, 2015b, p.16). Five enablers hence are considered relevant in order to establish sharing economy concepts: technology, culture, environment, regulation, and institutional authority. The following sections provide a closer look at the information about these enablers within the reviewed literature.
Technology as an Enabler
Technology, and the Internet in particular, have fundamentally changed interpersonal behaviour such as the way we connect and communicate with each other. With regard to economic activities, transactions and exercising of our purchasing power have been radically transformed (Clements 2014, p.107). More specifically, Dervojeda et al. (2013, p.12) refers to the increasing degree of familiarity of most people with various online activities. A growing trust in online transactions is considered a general enabler of any peer-to-peer online platform. She also mentions a lot of hesitation of early eBay users to provide the novel online marketplace with their credit card details, which was only ten years ago. Today, modern networks and devices such as smart phones and tablets allow us to use a wide range of digital payment methods in a convenient and time-saving manner. Most of such activities in the online world are, moreover, tracked and analysed in order to obtain more information which facilitates further interconnection of our society. What is more, most large corporations such as Amazon, Google and Facebook develop “[…] track our history, and use sophisticated algorithms to predict our future buying preferences” (Clements 2014, p.108).
With regard to the sharing economy, the usage of applications and social media may result in a systematically increasing trend of social connectivity, online marketplaces and transactions. The opposite position is described by Turkle (2011, pp.1-20) as a detrimental illusion of connectivity, online, at the cost authentic interpersonal relationships with other people in the real world. The startling observations she made throughout her research was that for a large proportion of the young generation, such psychological issues increase proportionately to the time spent on connecting with people online Turkle (2011). Therefore, some sharing economy models that involve meeting people, could be seen as an opportunity to decrease the isolation and loneliness that some people are suffering from. Her perspective according to which technology can be alienating stands in strong contrast the notion bringing people together introduced by Botsman and Rogers (2010). Both have solid and reasonable arguments and need to be considered accordingly with respect to individual use cases of the sharing economy.
Furthermore, such behavioural changes induced by continuous utilisation of technology, along with other social factors, lead to a notion of culture which is also considered as an enabler of the sharing economy.
Culture
Factors such as economic rebalancing, material efficiency, technological change and high-speed domestic adoption (Gawel, Machur and Pennington, 2016, p.4) do all have a certain impact on the culture of our society. For this reason, Dervojeda et al. (2013, p.15) considers culture as key for the adoption of peer-to-peer market systems. Culture has a strong influence on whether or not business models are accepted across different communities. Despite the before mentioned positive disposition towards technology, customer acceptance may remain a challenge for almost all peer-to-peer platforms since they typically differ strongly established practices (Dervojeda et al. 2013, p.15). Regarding some businesses that are trying to establish a sharing economy platform, Gawel, Machur and Pennington (2016, p.11) suggests that efforts for actively developing a subculture within the targeted communities might be advisable. But with the aforementioned broader notion of culture, another enabler of the sharing economy of global significance might be deduced – environment.
Environment
The Sharing economy allows societies to provide and manage infrastructure, resources and services in a much more efficient manner. From this observation, Vinod Kumar and Dahiya (2017, pp.42-43) conclude that the urban environment and its accumulated consumption is managed more efficiently as well – including natural resources. Peeters et al. (2015, p.21) mentions prospective benefits to environment and sustainability derived from the concepts for sharing assets. In this context, Sundararajan (2016, p.65) also point out the environmental friendliness which comes with the before mentioned efficiencies of renting over owning. He also refers to the ecological damage caused by production and distribution of new goods. With regard to smart cities that include a range of already existing sharing economy concepts, Vinod Kumar and Dahiya (2017, p.946) suggest that the long term reduction of CO2 emissions enhance environmental sustainability. This outlook of low-carbon cities does, however, not only involve a successful implementation of collaborative consumption, but rather a set of technological, behavioural and, subsequently, regulatory changes. The latter of which is going to play a crucial role for the sharing economy in general and hence is examined within the following section.
Regulation
From the perspective of the European Commission, Dervojeda et al. (2013, p.14) refers the general issue of a lack of specific legislation for sharing initiatives across different industries. More specifically, they describe the existing legislation as not clear enough concerning several sharing economy concepts. In addition to the lack of clarity, another legal issue affecting models from various industries relates to the blurry lines between individuals and businesses. For instance, how to determine whether peers who rent rooms in their homes are merely engaging in sharing, or can be considered small hotels. This vagueness leads to friction and certain difficulties among the three groups of key players involved in such P2P models – consumers, businesses and institutions as mentioned in section 2.2.2. (Demary 2015, p.15).
According to Sundararajan (2016, pp.131-139), new forms of market failure could occur as a consequence of an ineffective distinction between the personal and professional nature of supply. Therefore, Dervojeda et al. (2013, p.15) suggest that having “[…] minimum safety and quality standards” might have a positive effect on consumer protection (Sundararajan, 2016, p.131) and the participation in peer-to-peer activities. In this context, future regulations should focus on peer-regulation, self-regulatory organisations and data-driven delegation (Sundararajan, 2016, p.131). Furthermore, and with regard to sharing intangible assets such as time and skills, Dervojeda et al. (2013, p.15) recommends “[…] policy measures that facilitate the availability of entrepreneurial software developers and programmers […]” in order to propel the development of new platforms for the coordination of sharing activities. They give an example of policy makers who provide tailored tenders for the purpose of encouraging innovation within start-ups.
However, a survey conducted by PwC (2015b, p.16) of consumers from the US reveals that two thirds of the respondents consider peer-regulation more important than government regulation. Moreover, almost 70% say that they may only engage in such sharing activities if some they trust explicitly recommends it.
Ultimately, regulatory approaches are supposed to appropriately address and coordinate those socio-economic drivers and enablers that require a regulatory framework in order to have primarily positive effects to the greatest possible extent (Deloitte, 2015). However, achieving the before mentioned goals may not necessarily require more regulations, but could also be achieved by reducing regulatory barriers and constraints of individuals. The subjects of discussion around regulation in sharing economies as well as findings from surveys indicate that trust among the consumers (supply and demand) within peer-to-peer systems might play a crucial role for its expansion and success. Thus, the following section provides an examination of institutional authority as an arbiter of trust followed by a first look on the concept of centralised trust versus decentralised trust.
Institutional Authority
Trust is understood as being confident in a person, entity or quality as well as the ability to rely on the information provided by such agents (Oxford Dictionaries, 2017). With respect to the regulatory issues around facilitating trust among the players of sharing economies, PwC (2015b, p.16) describes platforms and peer-review systems as arbiters of quality, reliance, and brand-based trust.
According to Sundararajan (2016, p.131-139) the core issue lies in information asymmetry which is typically reduced through rules, laws and constitutions imposed on businesses. Brands are considered “economic institutions” which indirectly provide trust to sharing economy platforms by establishing rules which its participants have to follow along with ratings and reviews about how well they comply and perform. Another, rather informal, constraint might come from norms of behaviour that a society agrees upon (Sundararajan, 2016).
Botsman (2017) points out a shift of trust from institutions to individuals. In this sense, she also refers to the before mentioned accustomed utilisation of ratings and reviews for quality of products, services and the respective suppliers as a whole. She continues by making clear that this disruptive development is not solely enabled through technology, but primarily relates to a profound shift in trust. In the following section, different perspectives on trust are compared in the context of sharing economy, followed implications for the future of institutional authority and trust.
From the regulatory perspective, Dervojeda et al. (2013) advocate granted trust certificates for platforms, in order to entitle the respective companies as trust arbiters for peer-to-peer activities. Botsman (2017) critiques such an institutional mind set by disagreeing with the general appropriateness of traditional top down approaches in terms of managing trust in organisations and brands as well as governance of peer-to-peer market systems.
Both, Sundararajan (2016) and Botsman (2017) challenge the future role of brands in peer-to-peer market systems in particular. Such notion of brand-based trust might carry significantly less weight as it was designed to “[…] serve an industrial model of supply and demand, and not one that includes distributed networks, online systems and digital platforms” (Botsmann 2017, p.198). Further dimensions of trust, shown in table 2, illustrate the important role of trust, as it illustrates that trust not only relates to the institutional context of governments, but also for broader notions such as cultural dialog. Her recommendation to boards and management is to adapt to the shift in trust and to actively search for new tools which enable alternative approaches to trust within sharing economies (Botsman 2017). In other words, the traditional models of trust that are based on audit, regulation, insurance, and contracts all refer to an essentially centralised concept of trust. However, the idea behind exchanging usage rights for assets as well as services within a peer-to-peer market structure is a primarily decentralised one.
Table 2: Many Faces of Trust in Sharing Economy
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Source: Sundararajan, 2016, p.150
With regard to the economic crisis and emergence of the sharing economy in the US in 2009 (in the EU around 2013), Demary (2015, p.8) points out the loss of trust in the banking segment as well as large corporations. Although the newly founded companies and their P2P models were based on trust even more, the aforementioned loss apparently had no influence on the new companies and platforms. A suggested reason is, that since the bilaterally or multilaterally relationships between consumers are at the centre of trust-sensitive transactions. Moreover, Demary (2015, p.8) utilises the term “prosumers”, due to the simultaneous consumption and production among individuals who are collectively considered consumers within a sharing economy. As a result, the companies have moved into the background by merely providing an infrastructure for a) information exchange and coordination, b) financial transactions, and c) trust-oriented rating systems where prosumers rate each other in order to reduce the information asymmetries.
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