Amsterdam Business School | University of Amsterdam
How does the transformative value of cloud computing contribute to the ecosystem value of Sharing Economy multi-sided platforms?
Name : Steven van Dongen
Student number : 10737618
Supervisor : Jeroen Kraaijenbrink, PhD
Date : 15-07-2020
2 Statement of Originality
This document is written by Steven van Dongen who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
We’re living in a digital age where new digital technologies drive opportunities and give birth to new business models being developed. This includes the emergence of the multi- sided platforms. Although sharing resources is a very old and ancient virtue, the Sharing Economy fueled by the emergence of these multi-sided platform became a rather recent phenomenon. Cloud computing is widely recognized as a technology game changer and often referenced for its IT value for business but far less recognized for its transformative and value-creating capacity for business and impact on the ‘real-world’. These two topics merged together raised the following question to be researched: How does the transformative value of cloud computing contribute to the ecosystem value of Sharing Economy multi-sided
platforms? Based on extant literature a conceptual framework was develop linking embedding four propositions to frame the research. A qualitative research was done by means of a multi- case study interviewing seven Dutch sharing platform supported by secondary data. Coded data was analysed within case and cross-case to search for patterns and find answers to the request question. Result that was found is that sharing platforms propositions do benefit when the platform is built based on cloud computing techniques. The transformative mechanisms of cloud being decoupling, platformization and recombination all contribute to the
transformative value by providing the foundation of all key components that make a sharing platform proposition. The key components are a matchmaking solution, external resources governance mechanism, innovation model and a stakeholder management system.
Table of contents
Abstract ... 3
1. Introduction ... 6
1.1 IT the engine room for change and transformation ... 6
1.2 New IT technology wrapped into great new business model ... 7
1.3 Sharing Economy multi-sided platforms ... 9
1.4 Maximizing ecosystem value ... 10
1.5 Research question ... 11
2. Theory ... 13
2.1 Key concepts ... 13
2.1.1. Transformative value of Cloud computing ... 13
2.1.2. Multi-sided platforms ... 15
2.1.3. Sharing economy ... 16
2.1.4. Ecosystem value ... 17
2.2 Business model innovation through recombination ... 17
2.3 Ecosystem governance ... 19
2.4 Smart seamless interactions ... 21
2.5 Peer-review, access and openness ... 23
2.6 Research ... 24
2.7 Contribution ... 25
3. Research methodology ... 26
3.1 Research design ... 26
3.2 Sample ... 27
3.3 Interview and data collection ... 28
3.4 Data analysis ... 29
4. Within-case results ... 32
4.1 Case 1: Peerby ... 32
4.2 Case 2: FLOOW2 ... 34
4.3 Case 3: Flitsmeister Pickup ... 36
4.4 Case 4: Stapp.in / Vecore ... 39
4.5 Case 5: ClickmyBrain ... 42
4.6 Case 6: Interveste, Club van vrijwilligers ... 45
4.7 Case 7: Grutto (koopeenkoe.nl) ... 47
5. Cross-case results ... 49
5.1 Adapting to demand of the sharing market (P1) ... 50
5.2 Governance of the ecosystem (P2) ... 51
5.3 Effective matchmaking of sharing interactions (P3) ... 54
5.4 Building trustful relationships with stakeholders (P4) ... 56
5.5 Other cross-case findings ... 58
5.5.1 Ecosystem value ... 58
5.5.2 Ubiquity thoughts ... 59
6. Conclusion ... 60
6.1 Conclusions and answer to the research question ... 60
6.2 Implications for extant theory ... 62
6.3 Practical implications ... 62
6.4 Limitations and future research ... 63
References ... 65
In print ... 65
Online media ... 68
Appendix 1 – Sharing economy business model categories (Laukkanen et al.,2020) . 69 Appendix 2 - Interview protocol ... 70
Appendix 3 – Code tree ... 73
Appendix 4 – Codes vs Propositions ... 74
Appendix 5 – Variable values ... 75
Appendix 6 – Coding frequencies ... 76
“Digitalization is the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a
digital business” (Gartner IT Glossary).
1.1 IT the engine room for change and transformation
We’re living in a digital age. The accelerated speed of development of new digital technologies of the last few decades drive new business opportunities and give birth to new business models being developed. Daniel Burrus (2016) acknowledged the “Three Digital Accelerators” in 1983 by adding Digital Storage and Digital Bandwidth to the computer processing power known in Moore’s law as accelerators. He claims that today the Three Digital Accelerators have reached a point of exponential change that is creating dramatic change in very short periods of time and which has huge implications on business strategies and the managing of risks (Amit & Zott, 2008). Not long after the global introduction of the World Wide Web in the end of last century, “E-business”, referred to by Amit & Zott (2001) as business conducted over the internet, became the early challenge in the digital journey for firms which went beyond Web 1.0 which primarily involved one-directional provision of information to consumers who did not interact or respond to the website or to one another (Belk, 2014). Doing business over the internet rapidly emerged into an online interactive activity where value can be created by the ways in which transactions are enabled. In a more recent article Zott & Amit (2007) acknowledge the shift in perspective from viewing
organization form as a complement to IT investments toward viewing IT as an enabler of boundary-spanning organizational design (Bharadwaj et al., 2013). In a recent desktop study performed by Diemé and Amadi-Echendu (2015) on trends in computing and associated business models they state that cloud computing is the next step in the evolution of ICT. It constitutes the future of ICT and that of the internet, called fifth generation of computing after
7 mainframes, personal computers, client servers and web services respectively (Rajan and Jairath, 2011). They found that cloud computing reaches its maturity now users are getting a higher level of understanding and associated risk, such as security concerns, are becoming manageable. Cloud computing is defined as “a model for enabling ubiquitous, convenient, on- demand network access to a shared pool of configurable computing resources [..] that can be rapidly provisioned and released with minimal management effort or service provider
interaction” (Benlian et al., 2018 & Mell et al., 2010). Cloud computing is linked to the continuing digitalization process and IT would continue to be the engine room for change and transformation (Diemé and Amadi-Echendu, 2015). For example, it may provide benefits when incorporated into established (mechanical engineering) products and services (Bharadwaj et al., 2013). According to Berman et al. (2012) cloud computing is widely recognized as a technology game changer (Evans and Schmalensee, 2016) but although rising its potential for driving business innovation remains virtually untapped. Benlian et al. (2018) observed undiminished interest in cloud computing but also noticed that focus of research has been primarily on adoption, operational issues and cloud computing impacts on IT value but far less attention to the transformative and value-creating capacity of cloud computing.
1.2 New IT technology wrapped into great new business model
Today, innovation must include business models, rather than just technology (Chesbrough, 2007).
It’s not just the digital technological innovation that drive business change. As stated by the Gartner definition it is the use of the technology woven into a business model and to become a digital business. Studies show that digitalization process requires to also rethink and change the business model of corporations (Björkdahl, 2009; Chesbrough and Rosenbloom, 2002; Calia et al., 2007; Chesbrough, 2007; Gobble, 2014). Gobble (2014) describes in her article ‘Business Model Innovation’ that smart companies are able to not only come with a
8 great new technological innovation but are also able to wrap it into a great business model:
“Now more than ever, it’s not sufficient to create a great product; truly innovative companies have to think deeply about – and repeatedly rethink – what value they deliver and how they can capture a portion of that value for themselves” (Gobble, 2014). A growing interest in business model innovation is noted she says. A review provided by Zott et al. (2011) reveal that there’s no common agreement on what a business model is and that literature is largely developing in silos. Nonetheless the authors found four emerging common themes among scholars of business models:
1. The business model is emerging as a new unit of analysis;
2. Business models emphasize a system-level, holistic approach to explaining how firms
3. Firm activities play an important role in the various conceptualizations of business models that have been proposed;
4. Business models seek to explain how value is created, not just how it is captured (Zott, Amit and Massa, 2011).
Chesbrough (2007) puts it this way: “At its heart, a business model performs two important functions: value creation and value capture” and Johnson et al. (2008) chime in by stating that a business model creates and delivers value. To their point of view a business model consist of four interlocking elements to do so: Customer Value proposition (CVP), Profit formula, key processes and key resources, of which the CVP by far is the most important. It shows similarities with the well-known Business Model Canvas developed by Osterwalder & Pigneur (2010) which describes a firm's or product's value proposition, infrastructure, customers and finances by depicting 9 building blocks. Among the different business models Osterwalder and Pigneur (2010) studied, they identified the multi-sided platform (MSP) as one of the business models that show patterns of similar characteristics,
9 arrangements of building blocks or behaviors which brings together two or more distinct but interdependent groups of customers. Such platforms are of value to one group of customers only if the other group of customers are also present. The multi-sided platform creates value by facilitating interactions between different groups and grows in value by the network effect (Katz and Shapiro, 1985). Evans and Schmalensee (2016) claim that six Information and Communication Technologies1, including cloud computing, have a turbocharging effect on multi-sided platforms, a business model with ancient roots, by reducing the cost, increasing speed and expanding scope of virtual connections (Amit & Zott, 2001). These MSPs operate as matchmakers with two or more different customer groups that meet and create transactions.
The matchmaker succeeds to identify and solve specific frictions in the market with their digital business model. Van Alstyne et al. (2016) assert that the MSPs, which they refer to as platform business models, are actually introducing new rules of strategies. Platforms are centered around interactions between two or more participants in an ecosystem in contrary to traditional ‘pipeline’ business models which are established around a core business process they claim. The structure is to be an infrastructure that will enable interactions and the repeated goal is to improve the quality and quantity of interactions (Van Alstyne et al., 2016;
Choudary, 2016; Evans and Schmalensee, 2016).
1.3 Sharing Economy multi-sided platforms
The rise of these MSPs also gave a boost to The Sharing Economy (Belk, 2014;
Laukkanen et al., 2020) where a core interaction enabled by infrastructure, the platform, connects customer groups to make value by sharing their excess capacities of products and services. This Sharing Economy can be defined as a socio-economic ecosystem (Wosskow, 2014; Belk, 2014; Hamari, Sjöklint, & Ukkonen, 2015). Firms such as Airbnb and Uber but
1Six Information and Communication Technologies are: more powerful chips, the internet, the world wide web, broadband communications, programming languages and operating systems and the cloud.
10 also Snappcar are well-known examples of this Sharing Economy platforms which are
characterized by overlapping roles of producers and consumers (Ritter & Schanz, 2019). The Sharing Economy platform business models have major implications for our traditional management and economic theories and practices (Evans and Schmalensee, 2016) and will assumingly reshape them. Laukkanen et al. (2020), using ‘an umbrella’ construct and a broader meaning of the Sharing Economy, categorized 13 Sharing Economy business models (SEBMs) mapping them against three foundational cores (Acquier et al., 2017) of which one is the platform. They refer to business models that focus on decentralized exchanges between peers through digital platforms (Laukkanen et al., 20020; Acquier et al., 2017). In its
‘Consumer Intelligence Series’ about ‘The Sharing Economy’, PWC (2015) also identifies digital platforms that connect spare capacity and demand as one of the core pillars. Other pillars it identifies are: transactions that offer access over ownership (Van Alstyne et al., 2016; Laukkanen et al, 2020), more collaborative forms of consumption (Belk, 2014), branded experiences that drive emotional connection (Amit & Zott, 2001).
1.4 Maximizing ecosystem value
(SE)MSPs introduce new rules of strategies (Van Alstyne et al., 2016) and are revolutionizing economy (Evans and Schmalensee, 2016). When comparing traditional business and (SE)MSPs Van Alstyne et al. (2016) emphasize the importance of implementing a value capture structure that maximizes ecosystem value instead of focusing on consumer value alone (de Oliveira et al., 2017). Focus is no longer on controlling the firms resources but on orchestrating the resources of the stakeholders within the network, on an outcome-, demand-driven model instead of consumption-, supply-driven model, on management of information and interactions between distinct groups creating ecosystem value instead of focus on the customer value (Choudary, 2016; Van Alstyne et al., 2016; Evans and Schmalensee, 2016).
11 1.5 Research question
Even before the inception of the modern–day cloud, Amit & Zott (2001) already observed that in e‐business, business conducted over the internet, new value can be created by the ways in which transactions are enabled. They developed a model of the sources of value creation which suggests that the value creation potential of e‐businesses hinges on four interdependent dimensions, namely: efficiency, complementarities, lock‐in, and novelty. The potential value of an e-business depends on the combined effects of all these value drivers they assert. The authors performed their research at an early stage of business conducted over the internet. Current modern-day cloud computing is linked to the continuing digitalization process according to Diemé and Amadi-Echendu (2015) while both Berman et al. (2012) and Benlian et al. (2018) argue that although indeed rising, its potential for driving business innovation remains virtually untapped, especially in the area of the transformative and value- creating capacity of cloud computing to impact real-world layers. That is, the value-creating potential for the ecosystem of the SEMSP. Compared to the research of e-business in general by Amit & Zott (2001), this research will focus on a specific digital business model, the SEMSP. It will also focus on cloud computing instead of IT technology in general and how it contributes to the creation of ecosystem value of the SEMSP. Hence, the research question of this paper is:
How does the transformative value of cloud computing contribute to the ecosystem value of Sharing Economy multi-sided platforms?
A qualitative research will be performed to find answers to the research question by means of a multi-case study. To guide this research, propositions based on extant literature were developed in chapter 2 followed by a detailed elaboration of the chosen research method in chapter 3. The next two chapters will describe the findings and analysis of the qualitative research where chapter 4 will discuss each single case and chapter 5 the cross-case analysis.
12 Chapter 6 will continue to discuss the results of the analysis by answering to the research question and the impact it has on extant theory, any practical implications and conclude with limitations and suggestions for furthers research based on the findings of this research.
2.1 Key concepts
A better understanding of the concepts that are part of the research question is required. This paragraph will elaborate on the concepts of transformative value of cloud computing, multi-sided platforms, sharing economy and ecosystem value.
2.1.1. Transformative value of Cloud computing
Cloud computing is an evolution of computer technology and a dominant business model for delivering information technology (IT) infrastructure, components, and applications. With cloud computing, a product-centric model for IT provisioning is transformed into a global, distributed, service-centric model, leading to a disruptive shift from IT-as-a-product to IT-as- a-service (Benlian et al., 2018). This can be interpreted as a rather technological phenomenon.
However, the cloud computing concept as defined in the research question is related to the value creating capability it has for businesses. Berman et al. (2012) conducted a research suggesting that while cloud computing is widely recognized as an important technology, relatively few organizations today actively embrace it to drive business model innovation.
Benlian et al. (2018) observed undiminished interest on technology as well but also far less focus on the transformative and value-creating capacity of cloud computing. Both recognize the value creating capability of cloud computing for businesses. Benlian et al. (2018)
presented a framework for research, the Transformative Impact of cloud computing (TICC) framework to guide future research in cloud computing which delineates IT Value from transformative value. It describes three key mechanisms: decoupling, platformization and recombination of services. After evaluating these transformative mechanisms from the technical layers of computing (infra resources, components, applications) they analyzed and extrapolated how the transformative mechanisms lead to impact on individuals, organizations and societies/economies, referred to as the real-world layers. Decoupling describes a process
14 in which one element of a system becomes an independent service with a defined service interface such that internal changes in this service will not disrupt the functioning of other dependent elements. On cloud infra and component level decoupling is enabled by
respectively virtualization and modularization and on application level it leads to separation between provider and users. Looking at the real-world layers the benefits can be characterized by attributes such as flexibility, ubiquity and accessibility (Benlian et al., 2018).
Platformization mechanisms build on decoupling and characterizes the process in which an entity (a provider organization) creates access and interaction opportunities centered around a core bundle of services (the platform) within an ecosystem of consumers, complementors, and other stakeholders. On cloud infra, components and application level platformization has led to the commercialization of respectively IaaS, PaaS and SaaS. On higher real-world layers platformization creates new ecosystems of value linking multiple stakeholders and
emphasizing concepts such as transparency, elasticity and agility (Benlian et al., 2018).
Recombination, the third transformative mechanism, refers to the process in which innovation potential is generated by combining cloud services and integrating them with other
transformative technologies within and across platform ecosystems. On all technical cloud layers this takes place by allowance of third parties products and services. This includes offering of basic third-party infra resources on IaaS platforms, third-party components on PaaS platforms through application programming interface (API) and third-party apps on SaaS platforms. On the real-world layers recombination fosters concepts such as innovation, co-creation and openness. Cloud computing provides the infrastructure to integrate smart objects and devices, enabling artificial intelligence that makes organizations more efficient, productive and responsive (Benlian et al,. 2012). Berman et al. (2012) illuminated six
business enablers of cloud computing that power business model innovation: cost flexibility, business scalability, market adaptability, masked complexity, context driven variability and ecosystem connectivity.
15 2.1.2. Multi-sided platforms
Multi-sided platforms coordinate the demand of distinct groups of customers who need each other in some way (Evans, 2003). Customer Value Proposition of a MSP arises from solving a friction in the market that keep participants in the market from dealing with each other easily and directly (Evans and Schmalensee, 2016). By solving the friction of the market, transaction costs and information asymmetry issues between producers and
consumers are reduced (Amit & Zott, 2001). The chief assets are information and interactions which together are also the source of value they create and the competitive advantage (Van Alstyne et al., 2016). Indirect network effects require to solve the coordination problem or so- called chicken and egg problem as the size of the one group will determine attractiveness for the other and vice versa. Both groups need to be developed together and since benefits will rise with the volumes, (SE)MSPs have to secure a critical mass in order to ignite (Evans and Schmalensee, 2016; Van Alstyne & Parker, 2017). Growing the network where both groups are in balance can be rather complex, especially when starting or entering new markets and the numbers are still low. Platforms require a thick market. Not just more participants but they must also do want to interact with each other. The chosen profit model will also impact the network effect as a right chosen profit formula may have a positive effect on the development of the network (Van Alstyne & Parker, 2017). The platform owner may for instance decide to make a distinction between a subsidy side and a money side for their customer groups. MSPs create ecosystems for which Van Alstyne et al. (2016) recognize a basic structure for
(SE)MSPs comprising of four types of players: owners, providers, producers and consumers.
The owners of platforms control their intellectual property and governance. Providers serve as the platforms’ interface with users. Producers create their offerings, and consumers use those offerings.
16 2.1.3. Sharing economy
Sharing economy can have a broad definition. Acquier et al. (2017) position sharing economy as resting on three foundational cores: Access economy, platform economy and community economy. Based on these foundational cores Laukkanen et al. (2020) introduced a specified categorization of 13 different SEBMs. Since this research aims to examine the transformative value of cloud computing it only relates to the platform economy core meaning that the interactions are facilitated by the SEMSP. Sharing, but also collaborative
consumption practices using platforms are characterized by temporary access to goods and services without the transferring of ownership (Belk, 2014). Shared goods and services cover material (recovery and recycling), products (redistribution), product-service systems, space, money, workforce (time, skills), knowledge, education, data and information and the SEMSPs typically facilitate Peer-to-peer (P2P) sharing interactions which includes B2B sharing of resources (Laukkanen et al., 2020). Sharing Economy platforms are often characterized by overlapping roles of customers who can switch between producer and consumer roles by creating and delivering the value proposition (Ritter & Schanz, 2019). PWC (2015) researched SEMSPs in different industries such as Automotive and Transportation, Hospitality and Dining, Retail and Consumer Goods and Media and Entertainment and distilled three core values that characterize the Sharing Economy platforms:
Trust prevails based on peer reviews (not on one-to-one peer interactions) (Belk, 2014; Amit & Zott, 2001);
Quality matters! There is a trade-up wherein existing users may be more willing to pay (Van Alstyne et al., 2016);
Creating a seamless experience will be imperative for success enabled by flawless digital tools, elegantly simple search and seamless transactions (Evans and
Schmalensee, 2016; Amit & Zott, 2001).
17 2.1.4. Ecosystem value
Ecosystem connectivity and collaboration with external parties is actually found by Berman et al. (2012) as one of the main objectives for adopting cloud services and recognized as a major benefit as it can lead to improvements in productivity and increased innovation.
Platforms seek to maximize the total value of an expanding ecosystem in a circular, iterative, feedback-driven process. Sometimes that requires subsidizing one type of consumer in order to attract another type (Van Alstyne et al., 2016). Through sharing transactions customer of the platform can create economic value by renting out their resources for a certain amount. A well-known example of this is the platform of Airbnb where an owner of a house can make some money by letting unused rooms. Social value can be created as well according to Belk (2014) because of social interactions that are linked to the sharing interaction and forms of collaboration. SEMSPs have a potential to create sustainable value, i.e. to reduce
environmental load, increase social well-being and to provide economic benefits but despite of the potential, the economic, social and environmental effects are largely unknown
2.2 Business model innovation through recombination
The current advances in IT technologies have allowed the development of new ways to create and deliver value and have opened new horizons for the design of business models (Zott et al., 2011).
For firms to sustain Burgelman (1983) corroborated in the eighties already that both incremental innovations and radical innovations are important. Clayton Christensen (2013) distinguishes efficiency, sustaining and disruptive innovation while Keeley et al. (2013) identified ten types of innovations which are categorized in three main groups: Configuration, Offering and Experience. They all reckon that innovation should not merely emphasize a new
18 product technology but is about the creation of a whole, viable new offering which creates value for customers (Osterwalder and Pigneur, 2014) and solves problems that really matter.
In Schumpeter’s theory, innovation is the source of value creation. Schumpeterian innovation emphasizes the importance of technology and considers novel combinations of resources (and the services they provide) as the foundations of new products and production methods (Amit
& Zott, 2001). When it comes to business model innovation scholars increasingly are
acknowledging that firms can compete through their business models (Casadesus-Masanell &
Ricart, 2010) and where novelty primarily aims at creating new types of transactions, a novelty-centered business model refers to the conceptualization and adoption of new ways of conducting economic exchanges among transaction participants (Zott and Amit, 2007).
According to DaSilva et al. (2013), referring to cloud computing, it is a bare necessity to create a new business model to incorporate a disruptive technology. The statement Zott et al.
(2011) made about IT technologies (in general) producing business model innovation also holds true for cloud computing more specifically as argued by Berman et al. (2012) and Evans and Schmalensee (2016). Cloud computing is a strong transformational engine for innovation, co-creation and openness (Chesbrough, 2012) they claim. The TICC framework of Benlian et al. (2018) helps to identify how these turbo-charged, cloud driven new platform business models create transformative value to the higher real-world layers. Recombination, the third transformative mechanism in the TICC framework introduced by Benlian et al. (2018), refers to the process in which innovation potential is generated by combining cloud services and integrating them with other transformative technologies within and across platform
ecosystems. Recombination creates a plethora of new opportunities and offers new ways of co-creation (Blank, 2013). Berman et al. (2012) mention market adaptability as one of the cloud’s business enablers which facilitates rapid prototyping and innovation and helps speed time to market (Evans and Schmalensee, 2016). Furthermore, Benlian et al. (2018) assert that cloud computing enables the creation of IT value to businesses through the use of cloud
19 applications, components, and resources and because of the decoupling mechanism there is a huge opportunity for complementors to co-create products and add bundle of services to the platform. Complementarities, presented by Amit & Zott (2001) as one of the value enablers for ebusiness, are present whenever having a bundle of goods together provides more value than the total value of having each of the goods separately. This leads to the first proposition:
P1: Recombination mechanism of cloud computing, possibly amplified by the
decoupling and platformization mechanisms of cloud computing, empowers the SEMSP to be agile and adapt quickly to demands of the ecosystem through both incremental and radical innovations.
2.3 Ecosystem governance
Quality of matches between supply and demand on the SEMSPs are of great effect for the success of the platform. As said, according to Evans & Schmalensee (2016) it is not just a number game but more a matter of a developing a thick market where customer groups are willing to do business with each other. Too many mismatches on search results will diminish repetitive visits of the consumers and lower number of consumers will attract less producers on the other side, referred to as the coordination problem by Evans & Schmalensee (2016).
Conversely, the better the matches, the richer the data that can be used to find matches (Van Alstyne & Parker, 2017). According to Amit & Zott (2001) the value-creating potential of an e-business, this includes SEMSPs, is enhanced by the extent to which customers are
motivated to engage in repeat transactions (which tends to increase transaction volume) (Van Alstyne et al., 2016; Choudary, 2016). A critical strategic aim for platforms is strong up-front design that will attract the desired participants (Van Alstyne et al., 2016). Berman et al.
(2012) identified masked complexity as one of the business enablers of cloud computing to enable expanded product sophistication and more user simplicity. It provides a way for
20 platforms to ‘‘hide’’ some of the intricacies of their operations from end users and because complexity is veiled, a platform can expand its product and service sophistication without also increasing the level of user knowledge necessary to utilize or maintain the product or service (Berman et al., 2012). But although striving for simplicity it sometimes pays off to also invest in customers by educating them and help them to create more value. When they can create that value, the ecosystem wins (Malhotra and van Alstyne, 2014). Most successful platforms launch with a single type of interaction that generates high value even if, at first, low volume.
They then move into adjacent markets or adjacent types of interactions, increasing both value and volume (Van Alstyne et al., 2016). Expansion can be fueled by strong relationships within the network, huge customer base and data collected according to Van Alstyne & Parker
(2017). Understanding the relationships both within and outside the platform ecosystem is crucial to platform strategy they claim. Business scalability, another business enabler of cloud computing identified by Berman et al. (2012) allows platforms to easily scale its business operations. By allowing for rapid expansion of computing capabilities without concomitant capital investment, cloud technology enables a company to quickly benefit from economies of scale (Berman et al., 2012). Successful platform businesses tend to move aggressively into new terrain and reframe traditional industries in new ways with little warning (Van Alstyne &
Parker, 2017). Since business focus for SEMSPs is on growing the network other metrics than the traditional financial measures are relevant to assess a platform’s success and potential.
Beside the number of participants and interactions, metrics like engagement, interaction failure or match quality should be defined and monitored (Van Alstyne et al., 2016; Evans and Schmalensee, 2016). The aforementioned business enablers of cloud computing closely relate to the concepts of elasticity, transparency and agility which are tied to the platformization mechanism of cloud computing, hence the following proposition applies:
21 P2: Platformization mechanism of cloud computing will lower the barriers of
stakeholders of the ecosystem to collaborate and enables to increase their willingness to do business or share.
2.4 Smart seamless interactions
Virtual markets introduced the unique characteristics such as high interconnectivity, speed of information processing, and lack of geographical constraints. (Amit & Zott, 2001)
According to Choudary (2016) in the journey towards a digital business the real change is achieved whenever the core source of value or core source of consumer decision making is becoming digitized (Benlian et al., 2018). Competitive advantage is determined by how much data the focal firm is able to collect and own on the digitized object, the digital value in the industry. This will create an opportunity for a new business model (Amit & Zott, 2008). Digitization of buyer behavior, identity and trust, location and machine performance are examples of digitized sources of value which companies such as Amazon, Airbnb, Waze and GE built their platform business models on. Cloud computing, implementation of API’s (Application Program Interface) and use of data analytics and AI (Artificial Intelligence) are considered key resources of the platform business model (Osterwalder & Pigneur, 2010) interwoven into the platform infrastructure to enable valuable interactions and gather information. It is this bundling of services that characterizes the mechanism of
platformization. Rich information distilled from data will enable the platform via smart algorithms to make instant decisions for and around these digitized sources of value. These instant decisions are at the core of the process and aim to offer customers seamless,
personalized (Amit & Zott, 2001; Berman et al., 2012) service experiences. Creating a seamless experience for customers will be imperative for SEMSPs according to research of PWC (2015). The decoupling mechanism of cloud computing will make easy access and
22 provision on-demand available for customers (Benlian et al., 2018), and the cost flexibility that cloud computing brings introduced ‘pay as and when needed’ services (Berman et al., 2012). Seamless experience for customers relates to enablement of flawless digital tools, elegantly simple search and seamless transactions. Consumers want to just search, find and order what they are looking for from any device with a few simple clicks. As said, masked complexity is a powerful enabler of cloud computing to comprehend this. User-defined experiences and increased product relevance are enabled through context-driven variability, another business enabler of cloud computing identified by Berman et al. (2012). The context- driven variability provided via cloud services allows businesses to offer users personal experiences that adapt to subtle changes in user-defined context, allowing for a more user- centric experience (Berman et al., 2012). Because of its expanded computing power and capacity, cloud services can store information about user preferences, which can enable product or service customization they claim. Research of Amit & Zott (2001) found that enabling customers to customize products, services, or information to their individual needs in a variety of ways will enhance lock-in. In addition, many platforms use data-mining methods to personalize products, information, and services. This will further enhance transaction efficiency by enabling faster and more informed decision making according to Amit & Zott (2001). Context-driven variability not only applies to the demand side but also to the supply side which requires that best matches with resources of producers are made through
sophisticated algorithms as the coordination problem should be solved in a short moment.
Cloud computing also provides the backbone infrastructure for smart products and services.
Almost anything – person, object, process or service – can be become digitally aware and networked and made smarter through mountains of data gathers from various interaction into real insights using sophisticated algorithms and powerful supercomputers (Benlian et al., 2018). They claim that ‘information –based’ AI is helping organizations become more
23 efficient, productive and responsive (Benlian et al., 2018). This leads to the following
P3: Platformization mechanism of cloud computing enables effective matchmaking of collaboration and sharing interactions through information transparency and smart use of data.
2.5 Peer-review, access and openness
Digital firms can establish trustful relationships with customers (Amit & Zott, 2001) and by providing consumers with ease of use and confidence in decision-making, a company moves beyond a purely transaction-based relationship to become a platform for an experience that feels more like a friendship (PWC, 2015). Reputation and rating systems but also
testimonials (sharing photos and videos) help to build trust. In addition it helps to build a reputational economy making transactions between strangers safer and less uncertain (Belk, 2014). To a great extent, the viability of shared services hinges on the quality of review systems Malhotra & van Alstyne (2014) say because people rely on them to decide whether and what to purchase hence authenticating the validity of reviews is critical to prevent abuse such as posts of unfounded complaints by customers. Peer-review systems are to be integrated in the SEMSP through the use of cloud technology (Benlian et al., 2018). One other enablers for value is related to the question of who to grant access to the platform. Van Alstyne et al.
(2016) argue that platform owners must make smart decisions on whom to let onto the
platform and control what consumers, producers, providers, and even competitors are allowed to do there. The openness policy determines who can have access and what can be done.
There seems to be an optimum equilibrium for the level of openness. On the one hand letting as much participants as possible access the platform will grow the network effect, however it comes with a risk of some value-destroying effects as some participants with bad intentions or
24 bad behavior might be given access as well. According to Evans and Schmalensee (2016) platforms need rules to make sure people and businesses that participate on the platform behave themselves. Successful platforms nurture the, what they call “positive behavioral externalities” and minimize the negative ones, particularly by discouraging participants from behaving badly. Applying a too strict access policy may mitigate the risk of the destroying effect on the one hand but will definitely have a negative network effect. Platforms consist of rules and architecture and their owners need to decide how open both should be Alstyne et al.
(2016) claim. According to them an open architecture allows players to access platform resources, such as app developer tools, and create new sources of value. By opening up pieces of technology for instance, producers and providers tend to participate and take advantage of the possibility to co-create. This leads to the final proposition:
P4: Transformative mechanisms of cloud computing help to build a reputational economy which establishes trustful relationships with customers, between customers and with other stakeholders.
It is important for scholars and practitioners to understand how the three
transformative mechanisms (i.e., decoupling, platformization, and recombination) impact value on the real-world layers that go above and beyond IT value. (Benlian et al., 2018)
Although sharing resources is a very old and ancient virtue, The Sharing Economy fueled by the emergence of the multi-sided platform is a rather recent phenomenon which evokes questions to be researched. Benlian et al. (2108) mention ‘Contextualizing
transformative cloud computing impact in business ecosystems’ as one of the recommended topics for further research. To a certain extent this research can relate to that call since the
25 transformative cloud computing impact is researched in the specific context of the sharing economy. Based on the review of extant literature sources of value for the sharing platforms were identified for which the outlined construct is depicted as the conceptual framework in figure 1.
Figure 1: conceptual framework
This research can be a valuable contribution since it aims to address the gap of a better understanding of the transformative value contribution of cloud computing for the ecosystem of SEMSPs. These platforms are a relatively new phenomenon for which limited research is conducted. Through research of the transformative value of cloud computing for the
stakeholders of the SEMSPs and research of the identified value enablers contribution to the ecosystem value of cloud based Sharing Economy platforms, new knowledge will be added to total body of knowledge.
3. Research methodology
3.1 Research design
A qualitative research is performed to find answers to the research question by means of a multi-case study. Robert K. Yin defines the case study research method as an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used (Yin, 1984, p. 23). Because of the explorative nature of the research semi-structured interviews were conducted and an interview protocol was designed and prepared in alignment with the propositions that are subject to research. See appendix 2 for interview protocol. The structure of the protocol will help guiding the concepts that are to be investigated in relation to the research question. By snowballing technique additional questions can be made. To strengthen construct validity data triangulation was applied by collecting secondary data (website, reports, interviews, blogs, news) for each case.
For data analysis the flow model of Miles and Huberman (1984) as shown in the diagram below was used which shows the iterative character of the process as indicated by the lines with bi-directional arrows.
Diagram 1: Data analysis flow model, Miles and Huberman (1984)
27 3.2 Sample
The unit of analysis is the SEMSP as described in § 2.1.3 which for the scope of the research should also be originated in the Netherlands. The specified categorization of different SEBMs by Laukkanen et al. (2020) is used to define the SEMSP that are eligible for research.
These are all the SEBMs categories where the platform economy foundational core is true: 4, 5, 6, 7, 8, 9 or 13. See table 1 for an overview of the 7 SEBM categories with a description of their characteristics. Appendix 1 is showing a complete overview of the categorization of SEBMs by Laukkanen et al. (2020).
Table 1: SEBM category overview - platform economy foundational core only
Consulting some websites on the internet which keep track of and list sharing economy companies on a yearly basis showed that the number of actual SEMSPs that fall within the definition that is used for this research is rather low and estimated below fifty for the whole of the Netherlands. An initial list of potential SEMSPs for research was assembled and by consulting official websites of the SEMSPs, google search and LinkedIn a detailed contact list
28 was compiled of founders, owner or persons in a senior key role. Invites for an interview were mostly sent via LinkedIn and via direct email in a few cases. Being introduced by a mutual LinkedIn contact was found to be the most effective approach to get connected and schedule an actual meeting for the interview. Cold calling was never successful. Several interviewees explained that this is because they are asked for being interviewed almost on a daily basis. Table 2 shows an overview of all the SEMSPs that were consulted and interviews were conducted.
Table 2: Cases overview with interviewees
3.3 Interview and data collection
Per case 1-2 semi-structured interviews per SEMSP were conducted and were held with the founder and/or co-founder or person with a senior key function. Interviews took between 35-55 min. Interviews were all recorded and transcripts were made. Transcripts are saved on private secured location without access via the internet. Transcripts were coded with tool QDA- miner Lite. Next to the semi-structured interviews, secondary data was collected. Table 3 shows a summary of all collected data, both primary and secondary for each case.
29 Table 3: Data collection
3.4 Data analysis
Relying on the theoretical propositions (Yin, 1984) an initial set of codes, the code tree was derived from the propositions to assure that the data is linked to the propositions and pattern-linking is enabled. During coding, additional codes were added as some data couldn’t be linked to the initial codes. See appendix 3 for initial and final code trees.
Data was collected, coded and managed with the use of qualitative data analysis software QDA-miner Lite. All documents and some images were added in the software tool and by creating variables, attributes were attached to these documents that were uploaded helping to manage the data properly. A COMPANY variable was used to identify the case the data belongs to and the variable SAMPLE indicates whether it concerns primary or secondary data where with the TYPE variable a type could be selected from a predefined list, see
appendix 5 for an overview of the available types. Other variables used are the DATE
variable to indicate when the data was created, in case of primary data that was the date of the interview, in case of secondary data that was the date that the document was retrieved, the INTERVIEWEE variable to record the name of the interviewee (only for primary data), the GENDER variable (only for primary data) and the LOCATION variable to enter the physical
30 or virtual location of the place where the interview was held or url where the data was
retrieved from. A STATUS variable was added to manage the coding process, see appendix 5 for the values.
Data reduction and data display
Data display is a continual process (Miles & Huberman, 1984) and by exporting coding analyses from QDA-miner Lite, data was displayed in Microsoft Excel by creating overviews where data was organized in matrices; see an overview of coding frequencies in appendix 6. For data reduction both tools were used. While coding in QDA-miner Lite, for some codes comments were added to note memos but also to cluster same code with similar content. When exporting the Coding retrieval to Excel the comments column was exported as well. Reduction of data happened in several sequences. As said, the first part was done in QDA-miner Lite. The next step was performed in Excel by filtering per case, per category the code and check whether all information was summarized in a comment field. If not, a
comment was added to ensure that all pieces of information per code were at least once summarized in the comment field. The next step was to summarize and reduce all comments per category which would remove all the duplicate data which was recorded for different codes below the same category. Per case two columns remain with the category in the first column and the reduced data summarized per data topic in the second column. This case reduced data summary is used to describe each of the cases in Chapter 4.
By using text styles bold and underscore the data that stood out was emphasized and by merging all reduced summary dataset of all the cases in one matrix, per category the reduced data was displayed in a row for all seven cases. After removing redundant duplicates over the cases, through pattern matching the data per category was searched for
commonalities, comparative structures (Yin, 1984) and exceptional findings and described in
31 the summary field to list any cross-case findings. Chapter 5 describes the most significant topics of the cross-case analysis.
4. Within-case results
This chapter describes analysis of each of the seven cases that were researched in order of the first interview per case that was conducted. According to Eisenhardt (1989) this within-case analysis helps to cope with the deluge of data in the analysis by becoming intimate familiar with every independent case. This familiarity of each case could strengthen the cross-case analysis of chapter 5.
4.1 Case 1: Peerby
Peerby.com is a sharing P2P platform where neighbours can lend or rent products from each other. Solving the coordination problem was quite a journey according to the founder Daan Weddepohl which they were eventually able to solve when making the decision to move to a demand driven model on a very small scale, the neighborhoods, where a user of the platform posts a request on the platform for a certain product or service for a certain date. The platform sends the request to other Peerby members living in the same area, the neighbours, who can respond to the simple question whether they own the requested product. Responses are recorded by the platform. If positive, a match can be made following a few simple steps via the app on mobile device or PC. Negative responses are interpreted as ‘weak signals’ and also recorded by the platform and stored in the database. In that way the platform knows what a member has available but also what not. On the other hand members can also via queries enter what resources they have or have not available for neighbours to rent. This creates a long tail of products and services per member on the supply side of the platform. The platform uses a certain logic when sending requests to members by using batches of messages deriving from blocks of data being send per every ten minutes or so beginning with members living closest to the requester and basically continues until a match is made. A more complex logic was used at first but eventually evolved in the current logic. This is because Peerby uses the Lean Startup ‘Build, Measure, Learn’ method (Ries, 2011) and the flexibility of the cloud based platform enables to
33 pivot and improve user experience easily and fast. The platform recently moved from Amazon AWS to Digital Ocean which illustrates the decoupling mechanism benefits of cloud computing. Another benefit is the elasticity of the platform which will automatically manage instant heavy traffic of users which is often experienced after presence in national media such as a television broadcast. The underlying infrastructure is automatically scaled up and down optimizing the pay-per-use subscription cost for running the platform. Innovation is a continuous and important process for the firm and done through making combinations between in-house developed software with as many as possible cloud services from 3rd parties. Since there is no other business model where Peerby can copy from, the business model keeps on evolving and with small iterations all experiments can be tested fast and easy in a real life setting on the platform. One of the partners is Mailjet of which the mail service is heavily used, another is CM which provides payment services and SMS services to name a few examples of the key services embedded in the platform solution. One of the payment services used is a 1 cent transaction which is part of the validation check performed for new members. This is one of the methods used to manage participant access. A review system is not yet implemented as it doesn’t have top priority and also blogs are not actively maintained. The founder acknowledges that receiving feedback from customers through a review or reputation system can be valuable but not for the phase they are in now. Current phase still requires big steps forwards with regards to improvements, rather radical changes where review feedback would ask for smaller, more incremental steps which do not have the impact currently aimed for. Managing complaints and expel of members from the platform is still more or less a manually maintained process although some mechanisms measuring member behavior may be able to recognize return of expelled members. Necessity of fully automating the monitoring of participants behavior is simply not very high with the current volumes. Blogs of some heavy Peerby users tell that they do not only value the platform for the lending of goods but also value the ability to help others, create more awareness of the people living around them and even learn to know their neighbours and
34 contribute to a better world through reduction of waste. This was actually one of the main reasons of the founder to start the Peerby platform. To make a contribution to the circular economy and also create ecological value. And although receiving praise even on a global platform the reality is often harsh because of a conflict between long-term ecological, social and environmental aims of the sharing platform ambition versus the short(er) term financial benefits of the investors.
4.2 Case 2: FLOOW2
FLOOW2 is a sharing P2P platform where businesses can share their excess resources with each other and create multiple values by doing so. The platform originated from the idea that sharing has a place in the life cycle of circular thinking and that multiple values are created for the ecosystem of the platform. In contrary to linear business models which mainly focus on creating financial benefits, sharing business models create financial, ecological and social value for all stakeholders within the ecosystem says Kim Tjoa, one of the founders.
Besides that, the value is more equally distributed over all participants. The FLOOW2 platform is configured in a way that it can host different sharing propositions for different communities using their own website with their own layout, look and feel. One of the specific examples is PharmaSwap, a platform for pharmacies to exchange excess medicines and through that reduce waste and cost and increase the availability of medicines during periods of shortages, for example in a situation of a pandemic. The FLOOW2 platform is used in the core, but the users will only experience the PharmaSwap label. The FLOOW2 platform can also be incorporated in a companies’ website to host certain sharing services. An example of this is a solution built for VDL Groep which enables the different subsidiaries and locations to share capacity, equipment and materials. FLOOW2 has implemented a number of successful sharing platforms and solutions for companies and communities within the Netherlands and abroad. FLOOW2 found that matchmaking between demand and supply is done on a local
35 scale and therefore they focus on developing communities around businesses such as
businesses which are located on the same business park or are members of the same local business association. Members are registered onto the platform both as producer and consumer. An intrinsic motivation of the business member to be willing to share should actually already be present to make it really work. In most cases this requires another mind- set, actually a paradigm shift of businesses. The circular thinking and principles should become the new culture of the business, flow through all levels of the business and impact processes and functions. When resources are required, the question for the professional
workers should pop-up: can we rent from our peers within our sharing community? And when resources are unused: does someone in our sharing community use this? The FLOOW2 platform is based on a pull strategy and is not specifically designed to push members towards this new way of circular thinking. Although businesses respond positively to the circular thinking, reality is stubborn and intrinsic motivation is often very low. To solve this coordination problem FLOOW2 firm applies a top-down strategy for creating the
communities by collaborating with local government. They can set up initiatives to promote circularity and sharing concepts for business communities in their city. The FLOOW2 platform is then considered a tool where companies that make the strategic choice to start sharing are able to start using it. Mexico City is an example considering to set up such an initiative. Another top-down approach is applied for SME’s where promoted by head office internal sharing is implemented between country locations or local stores. The platform enables members to list their longtail of unused or excess resources together with their
availability schedule. This requires a function within the firm to maintain demand and supply.
The platform has an intuitive design which makes it easy for users to maintain their resource lists but also manage transactions. Dashboards are available on different levels from user, to community manager to generic platform level to be able to monitor transactions and
information. A new request will automatically be sent via mail to all members of the
36 community and making matches including contract administration and payment can all be done safe and secure via the platform. Since the platform is community based, the self-control mechanism prevents members from bad behavior but if needed members will be expelled after complaints by the peers. A review system is in place where members can rate the
transaction and add comments but it is not actively monitored for feedback since the company focus is still more on business development. When the platform will be more mature data analysis fed by the review system will become of more value. The FLOOW2 platform is always evolving and development of new or improved functionality is an on-going fast iterative process in order to stay state-of-the-art and competitive. Blockchain technology is an example of one of the technologies which is being adopted as expectation is that it will improve the transaction process by making it even more secure and transparent. Other contemporary technologies such as AI were put aside perceived as of no additional value for the platform. Third party cloud services are used were possible but can also be retired easily when showing to be of no additional value. One of the ambitions for the future is to open up communities for each other and create additional value through cross-sharing transactions through the FLOOW2 platform.
4.3 Case 3: Flitsmeister Pickup
Flitsmeister Pickup is a new sharing P2P service which builds on the existing
Flitsmeister platform which was founded in 2010. Flitsmeister currently has 1,7 million users in the Netherlands and gained a lot of knowledge on traffic movements of automobiles. With this knowledge, they started developing a new sharing business model where traffic
movements are linked to demand for parcel transport using the free car space of cars. The existing Flitsmeister proposition offers real-time traffic information from speed camera to traffic jam and the developed core logic of the platform for this can now also be used for the new sharing service. Besides that, the simple reasoning is that when a car is driving from A to
37 B anyway it might as well be used to pick up a parcel which needs to basically travel the same route. The driver of the car can earn some money and reduce travel cost with it while zero additional carbon dioxide is emitted for the transport of the package. To measure whether their users and shopkeepers are actually interested in the concept they created a landing page on their website to inform on the new service with the possibility to register for candidates.
The response was huge and very positive from the beginning and reason for Flitsmeister to prepare the next step which is to run the end-to-end service for a restricted designated area in the Netherlands. At the moment of interviewing the managing director Jort de Vries,
Flitsmeister was at the verge of kicking off the pilot. The pilot is used to check for completeness and learn whether coverage is good enough and what market penetration is required to balance out demand and supply and run the service effectively. The initial plan was to run the pilot for a couple of months to then roll-out to the rest of the Netherlands and in the meantime further develop the platform for the service. However, due to Corona pandemic hitting the Netherlands (just like the rest of Europe and many places in the world) causing people to stay at home in isolation gave a sudden boost to on-line retail sales and with that a boost to parcels shipments. Flitsmeister reacted quickly by making the strategic
decision to launch the new propositions earlier for the whole of the Netherlands and not wait for a fully completed proposition. This means that shopkeepers can enrol via the site and via a call back by a Flitsmeister team, registration is completed. The users on the other hand can fully automated register via the website or the app to become a Bezorgmeister (free
translation: ‘delivery meister’) providing personal information such as name and address details and bank account details. When a shopkeeper has a package to be delivered, the demand is made known to the platform via the website. The platform registers the demand together with the location and then searches for Bezorgmeisters in the area of the location who will all receive a notification on their app. When the demand is accepted by one of the Bezorgmeisters on the mobile app, the platform will send a pickup code and address of the
38 parcel pickup location. The Bezorgmeister will pick up the package by identifying to the shopkeeper with the provided pickup code and enters the destination in the app. When sharing the route with the shopkeeper in the app, the package can be followed via track and trace by the shopkeeper and the receiver. At the moment of delivery a drop code also provided by the platform closes the transaction. Due to the premature launch the actual payment module is not yet available on the platform so the Bezorgmeister needs to send a payment request directly to the shopkeeper by him/herself without the interference of Flitsmeister Pickup. This procedure will change at the moment that the payment service will be made available for the Flitsmeister app and platform. The current proposition also launched without a delivery insurance
coverage. Flitsmeister will add that as soon as possible they say in the news media. The cloud platform together with the use of the app and website makes a rather complex process
transparent and easy to understand and use for the users. This proposition is targeted on a same-day-deliver for short distance up to around 20 to 30 kilometres. A second variant of the proposition will be launched later and targets on a long distance or on-trip delivery where packages need to be delivered further away and not on the same day. These deliveries are expected to be typically delivered by people who daily commute between home and work location. The platform is collecting lots of data which is used for analysis and creating new insight which may lead to new additional services through new combinations and
optimizations. A dedicated team of developers is continues working in iterations of 2-3 weeks on improvements or new functionalities of the platform. Requirements are composed by both Flitsmeister and stakeholders giving feedback. If possible third party cloud services are used and embedded into the platform solution and some developments are done by their parent company. A peer review system is not available yet and has definitely not the highest priority although the Flitsmeister proposition successfully uses a review and rating system. It is likely that this system will gradually be used for Flitsmeister Pickup at a certain moment. There is no policy to expel users from the platform. Next to financial and ecological value, value for
39 the community will also be created by through reduction of traffic movements. When this sharing proposition turn out to be successful, additional sharing services can be created such as carpooling or some kind of taxi service de Vries says.
4.4 Case 4: Stapp.in / Vecore
Stapp.in started as a car sharing P2P platform with a focus on rural areas in the Netherlands outside the Randstad (megalopolis in the central-western Netherlands consisting primarily of the four largest Dutch cities (Amsterdam, Rotterdam, The Hague and Utrecht) and their surrounding areas) with the aim to create an experience based on a prepaid mobile subscription model without physical transfer of the car key. With an app on your mobile phone a user should be able to register, make a reservation and have access to the car and drive within 5 minutes. However, after starting Stapp.in founder Reinald Bronkhorst soon found out that the spawned sharing solution offerings together with cumbersome
contemporary procedures for renting cars was not going to help Stapp.in and solve the friction in the market. He soon founded Vecore in collaboration with a hardware- and a software company to develop the Vecore sharing platform for the B2B market. The fully loaded sharing label Stapp.in was then used to proof the concept and the potential power of the platform solution. The Vecore cloud based platform was developed together with a Vecore Smartbox to be installed in the asset, the vehicle and a mobile app for users of the sharing service to be used for making reservations but also as virtual key to have access to the car. To communicate safe, secure and fast between the platform, the smart box and the mobile app a state-of-the-art solid protocol was developed which comprises a unique combination of an own developed protocol extended with the existing MQTT protocol. This smooth
communication between devices offers a seamless experience for the users. With Vecore car dealers, lease companies or other automotive organizations are able to create or extend their proposition with the high standard full and secure car sharing service, even under their own
40 white label but also organizations such as homeowners associations and local governments can use the platform. The Smartbox in a car can have its own unique configuration and preferences per customer which also determines what and how much data is collected at the platform. Data generated by the smart devices is solely used by the platform to create the best service and not exposed to external markets. Data analytics are used for capacity planning per location. AI is not used at this moment. Information can be monitored on dashboards by customers, but also on other levels such as the Vecore platform manager level. Reservation management, one of the many modules of the Vecore platform, is organized in layers: Vecore, dealers, B2B customer and user groups. The asset can dynamically be linked to more user groups based on certain attributes such as timeslots. Different customers can exploit the same asset 24/7 and share certain timeslots. Via the intuitive app users can not only do reservations but also see availability in their area to find a car, bike or scooter that fits their needs and situation for that moment. Vecore platform offers tools to help coordinate matching demand and supply like relocation of assets. Although very complex it can be done by the platform manager in one click. Also the app has many configuration options that customer will use to deliver their service. This includes which check and validations should be performed by a user of that customer. This can be a driver’s license check, bank account validation but also a feedback option when a car is dirty. Vecore platform is always evolving and after moving to an agile way of working by the development team changes and improvements are released faster and more effective. Since third party cloud services do not always comply with the standard and can create lock in they are mainly used for non-critical functionalities. A few examples are Molly for payments, Zip code check, driver license check (in app), VWE, RDW and CJIB to check fines. In certain cases Vecore choses to develop that are available in the market themselves because requirement of tenders sometimes do not allow plugins for a SaaS platform. The Vecore platform can be accessed via API in order to enable customers to
transfer data and a special developed Software Developers Kit (SDK) offers the customers the