Ecosystem Theory

The ecosystem concept is derived from the biological sciences. Although there are limitless definitions for the term ecosystem, one of the most lucid was coined by a pioneer in the science of ecology, Arthur Tansley (1935), who defined an ecosystem as the interactive system established between biocoenosis (a group of living creatures) and their biotope (the environment in which they live). Central to Tansley’s (1935) ecosystem concept was the idea that living organisms were continually engaged in a set of relationships with every other element constituting the environment in which they existed. Ecosystems could, therefore, be described as any situation where there were relationships between organisms and their environment.

However, it was not until the 1990s that James Moore (1996: 26) applied ecosystem theory to business. Moore is rightly credited with being the first person to produce a formal definition of the business ecosystem. In fact, Moore produced two separate definitions, one for the biological ecosystem and one for the business ecosystem. Moore (1996) defined a biological ecosystem as a community of organisms that interacted with one-another and their environment. This included lakes, forests and tundra and all abiotic components (non-living) such as mineral ions, organic compounds plus the rainfall and other physical factors (climate). The biotic (living) components included primary producers, such as green plants, macro-consumers, such as animals (which ingested other organisms or organic matter) and micro-consumers, such as bacteria and fungi that broke down the organic compounds upon the death of other organisms (Moore 1996: 26)

Moore (1996) then produced his own definition of the business ecosystem which he referred to as an economic community that was supported by a foundation of interacting organisations and individuals that produced goods and services of value to customers who were also members of the ecosystem. The members of the community (organisms) also included suppliers, lead producers, competitors and other stakeholders. Over time, these community members would co-evolve their capabilities and align themselves with one another. The companies that succeeded in developing leadership roles would change over time, but the ecosystem leaders would be instrumental in curating the overall health of the ecosystem through the achievement of shared visions and mutually supportive roles (Moore 1996: 26).

There are strong similarities between these three definitions. Tansley (1935) refers to the existence of an interactive system between living creatures and the environment thereby implying the continuous engagement in relationships. Moore’s (1996) biological ecosystem definition also highlights the interaction between organisms and the environment, but he also refers to a community and the existence of a terrestrial food chain that generates energy within the system. In his business ecosystem definition, he also refers to the interaction between organisations and individuals and uses the term economic community, not just community. He also refers to a food chain or energy source which is the production and consumption of goods and services of value to customers. However, Moore takes the interaction element of the ecosystem to a new level when he refers to co-evolution, alignment, shared visions and mutually supportive roles. Finally, Moore also referred to the existence of leadership roles within business ecosystems. These are sometimes known as the keystone firms (Iansiti and Levien 2004) or the economic catalyst (Evans and Schmalensee 2007).

This approach is in stark contrast to the rational, industry structure approach analysed in Chapter 2 - particularly Porter’s Five Forces model (1980). In Porter’s framework, bargaining power and barriers to entry were the key determinants of success and monopolistic power was the goal, not co-creation, co-evolution or shared value involving a large community of participants or members. Moore (1996) also insisted that companies should be viewed not as members of a single industry but as part of a business ecosystem that crossed a variety of industries. This was one of the reasons for the blurring of industry and market boundaries along with new technologies. The concepts of co-creation, co-evolution and continuous innovation also brought a dynamic perspective to the ecosystem model which was absent from conventional economic models such as Porter’s Five Forces framework (1980).

Moore (1993), also stated that innovative businesses couldn’t evolve in a vacuum and that an ecosystem community was, therefore, better positioned to out-innovate firms operating within conventional mar- ket/industry structures or silos. The only truly sustainable advantage for a company came from out-innovating the competition at every stage of the ecosystem’s evolutionary cycle from Stage 1 (birth) to Stage 2 (expansion) as well as Stage 3 (leadership) but particularly in Stage 4 (self-renewal).

Despite the seminal nature of Moore’s (1993, 1996) business ecosystem theory, his research was undertaken before the Internet had gained any traction and did not, therefore, draw on any examples and evidence from online platform companies. The biological analogies used by the author were also very metaphorical and based on fragmented references to different types of terrestrial ecosystems (lakes, rivers, forest and grassland), and no single overarching biological ecosystem is used (Pickett and Cadenasso 2002). In Chapter 5, a deep-sea hydrothermal vent ecosystem is used to address some of these shortcomings (Van Dover 2000).

Marco Iansiti and Roy Levien (2004) also undertook important ecosystem research and identified an important difference between biological ecosystems and business ecosystems. They found that although a biological ecosystem was self-organising a business ecosystem did not necessarily follow a similar type of development. A business ecosystem frequently benefited from having a leader or what Iansiti and Levien (2004) referred to as a keystone. In fact, the authors identified four main types of ecosystem strategy which were the keystone, physical dominator, niche’ and commodity.

We will now look at each of these strategies in more depth starting with the keystone approach. The keystone strategy implemented by the keystone organisation played a very important role in improving the overall health of the ecosystem through the provision of a stable and predictable set-of common assets. Microsoft’s original personal computer operating system and Google’s Android mobile software and development tools

(that other organisations used to build their own offerings) were good examples of this. Keystones can also significantly improve ecosystem productivity by making it easier to connect network participants to one another or by facilitating the creation of new products by third parties. Ecosystem robustness is also enhanced by incorporating technological innovations as well as encouraging niche’ creation by making innovative technologies available to a wide variety of third party organisations. The opening up of ecosystems to third-party software and app developers is a very good example of this i.e. Microsoft in personal computer software (Gawer and Cusumano 2002) and Apple and Google in mobile apps. Iansiti and Levien (2004) also stated that by continually trying to improve the ecosystem as a whole, keystones sought to ensure their own survival and prosperity. As in biological ecosystems, keystones subsequently exercise a system-wide role despite being only a small part of their ecosystems’ mass (Iansiti and Levien 2004).

An effective keystone strategy consists of two aims. The first is to create value within the ecosystem. This is essential otherwise it will fail to attract or retain members. Second, the keystone must share the value it creates with other participants in the ecosystem. Google created value by giving away its Android mobile software to the telecoms operators. This resulted in a large ecosystem of customers who purchased cheaper Android- enabled handsets (which benefited hardware firms such as Samsung) and who also subscribed to mobile contracts for Android phones (benefiting the telecoms operators). This large user-base also enhanced the attractiveness of the software standard to app developers who became part of the ecosystem. These developers also received software development kits (SDKs or ‘devkits’) i.e. development tools to facilitate the creation of software applications for Android. The Android ecosystem is also an open system (open source software) as opposed to a closed ecosystem. This is the main reason for its enormous pervasiveness (more than 80 percent market share) compared to the Apple iOS mobile software ecosystem (over 13 percent market share) which is semi-closed or proprietary in comparison i.e. a ‘walled garden’.

The Android software acts as a platform which forms the foundation of Google’s mobile ecosystem. Iansiti and Levien (2004) described a platform as an asset in the form of services, tools or technologies that offer solutions to others in the ecosystem. Iansiti and Levien (2004) developed their definition further by saying that the platform could be a physical asset such as the efficient manufacturing capabilities that

Taiwan Semiconductor Manufacturing offered to computer chip design companies (that did not have their own silicon wafer foundries) or an intellectual asset such as the Windows or Android software platforms. The keystone, therefore, leaves the vast majority of the value creation to others in the ecosystem. However, the keystone must also retain some of the value that has been created for themselves. Google achieves this by capturing large amounts of data from the users of the Android software which is monetised in the form of advertising revenues - which also creates benefits for advertisers.

Keystone organisations must ensure that the value of their platforms increases sufficiently to cover the cost of creating, maintaining and sharing them with the ecosystem members who choose to use the platforms. This allows the keystone players to share the surplus with their communities. However, during the Internet boom, many businesses failed because - although the value of the keystone platform was increasing with the number of customers (theoretically) - the actual operating costs rose resulting in margin erosion and ultimate collapse (Abramson 2005).

This approach to strategy is in stark contrast to Porter’s Five Forces (1980) Industry structure paradigm. Unlike, Porter’s industry structure approach, there is no attempt to develop monopolistic rents through high bargaining power and the creation of barriers to entry. Instead of preventing entry and substitution (reductionism), the ecosystem approach is designed to increase the size of the community (expansionism) and its contribution to innovation, not to reduce it. This approach also contrasts with the resource-based view (RBV) of strategy where competitive advantage is achieved by firms developing superior resources and capabilities to competitors. These are resources that are owned and/or controlled by the firm, and there is a strong internal rather than external orientation. With an ecosystem approach, the keystone doesn’t primarily seek ownership or control but access to producer-consumer networks and enhanced value from a broader range of external capabilities (Parker et al. 2016) thereby inverting the resource-based view (RBV). The ecosystem approach, therefore, focuses on the co-creation and co-evolution of capabilities at an ecosystem level rather than at a firm or industry level (Teece 2012).

The physical dominator strategy resembles the traditional approach to strategy identified in Porter’s Five Forces model (1980) where players seek to gain some form of monopoly power or domination. Whereas keystones exercise indirect power, the physical dominator aims to integrate vertically or horizontally to own and manage a large proportion of a network directly (Iansiti and Levien 2004). Once a dominator takes control, this will impact negatively on the ecosystem, and there will be little opportunity for a meaningful ecosystem to emerge. Iansiti and Levien (2004) use IBM as an example and how the firm dominated the mainframe computing ecosystem. This strategy was effective because it allowed IBM to create and extract enormous value for long periods of time (Pugh 1995). However, it failed when the personal computer (PC) ecosystem emerged which was more open and distributed and was supported by keystone strategies from Apple, Microsoft, Intel and even IBM at the beginning.

Where a value dominator strategy is adopted, Iansiti and Levien (2004) stated the firm has little control over its ecosystem, occupying just a single hub in some cases. It creates little if any value for the ecosystem. A value dominator would extract as much as it could by extracting from the network most of the value created by other members. It would subsequently leave too little to sustain the ecosystem, which could ultimately collapse and bring the value dominator down with it. Although the digital music ecosystem has not shown any signs of collapsing there is evidence of value dominator strategies by key players such as Google’s You Tube music service which is supported by advertising. The monetary returns to artists and music companies are extremely small representing 40 percent of music played but only 4 percent of overall revenues (Financial Times 2016a). This is in contrast to streaming subscription services provided by firms such as Spotify which have generated $6billion in revenues for the industry (Financial Times 2016a). The only factor sustaining the ecosystem is the exposure that artists gain from their music being played on what is the largest global music platform. Another example is the cable TV industry in the US where cable companies have continued to charge high prices for poor services and inappropriate programming leading to a decline in subscriptions as customers migrate to the Internet (Financial Times 2015).

In business ecosystems, it is normal for most organisations to follow niche’ strategies. The purpose is to develop specialised capabilities that differentiate them from other companies in the network. These firms leverage complementary resources from other niche’ players or the ecosystem keystone. When they are allowed to thrive, niche’ players represent the bulk of the ecosystem, and they are responsible for most of the value creation and innovation. They operate in the shadow of a keystone which offers its resources to niche’ players (Iansiti and Levien 2004). Modern examples of niche’ players are the software development firms (apps), the small independent computer games companies (‘Indies’) and the microprocessor design firms (Arm Holdings).

According to Iansiti and Levien (2004), where innovation was low and relationships were less complex, commodity strategies would often prevail. The authors claimed that an ecosystem strategy was largely irrelevant in such instances since firms operated relatively independently of one another using price competition. Such strategies have been evident in the telecommunications sector where telecoms operators and cable companies have been slow to adapt to new technologies and have been competing on price rather than the development of new products and services. Only recently have these firms begun to move towards the provision of bundled quad play products based on content and high-speed broadband strategies. However, the broadband networks, speeds and mobile coverage still remain underdeveloped. The low levels of expenditure on R&D as a percentage of sales relative to other ICT ecosystem companies have resulted in commodity strategies emerging. This viewpoint is reinforced by an Ernst and Young report in 2014 entitled: Top 10 Risks in Telecommunications 2014. This revealed that telecoms firms were failing to adopt new routes to innovation and failing to realise roles in industry ecosystems (Ernst and Young 2014: 2).

It is also important to note that roles in ecosystems aren’t static. A company may be a keystone in one domain and a dominator or a niche’ player in others. For example, Microsoft was a keystone in the personal computer (PC) ecosystem but became a dominator in browsers and search (Arthur 2014). Microsoft implemented a platform envelopment (Eisenmann, Parker and Van Alstyne 2010) strategy (this occurs when a platform absorbs the functions and the user base of an adjacent platform) to win the browser wars with Netscape in the mid-1990s (Arthur 2014). Airbnb and Uber started as niche’ software apps but became keystones in online accommodation and transport respectively.

Meanwhile, the telecoms companies are trying to move away from commodity strategies to becoming value dominators as they upgrade their networks and threaten to introduce ad blocking software to monetise value from high data traffic from the media platforms they serve (Financial Times 2016b).

Finally, Iansiti and Levien’s (2004) research provides an important development of Moore’s (1993, 1996) original business ecosystem model. However, their work (although useful) was produced within the ‘shadow’ of the dot-com crash (Abramson 2005) and the analysis of technology architecture does not incorporate more recent technological developments in ICT such as Web 2.0, cloud computing and big data which have had a transformational impact on the growth of ecosystem platforms. Therefore, the chapter will now consider Martin Fransman’s (2010) work entitled: The New ICT Ecosystem: Implications for Policy and Regulation (Fransman 2010).

Fransman’s (2010: 9) research viewed the entire ICT sector as a system which he represented in an ecosystem layered model (ELM) consisting of four interconnected layers comprising the following (see Table 4.1):

  • 1) Networked element providers who produced items such as PCs, mobile phones and their operating systems including telecommunications switches, routers, servers and transmission systems.
  • 2) Network operators who create and operate telecoms networks including mobile, fibre, copper, cable TV and satellite networks.
  • 3) Content and application providers (including ICAPs) i.e. the Internet.
  • 4) Final consumers.

The interactions between the various firms in the New ICT Ecosystem’ were considered to be symbiotic. Symbiosis implied high inter-dependence between organisms (firms) which were mutually beneficial. According to Fransman (2010), the symbiotic relationships also existed within the layers of the ecosystem as well as within firms and between the various layers.

The Six Symbiotic relationships are summarised as follows (Fransman 2010: 37):

  • 1) Relationship between networked element providers and network operators.
  • 2) Relationship between network operators and content and applications providers.

Table 4.1 A simple ecosystem layered model - ELM (Adapted from Fransman 2010)

Level 4:

Final Consumers

Level 3:

Content & Applications - Internet Platform

Level 2:

Networks - Mobile, Fibre, Copper, Cable & Satellite

Level 1:

Networks - Switches, Routers, Servers, PCs & Phones

  • 3) Relationship between content and applications providers and final consumers.
  • 4) Relationship between networked element providers and final consumers.
  • 5) Relationship between networked element providers and content and application providers.
  • 6) Relationship between network operators and final consumers.

Fransman’s ( 2010; 2010) model is very useful in providing a number of beneficial insights. First, the model makes it possible to conceptualise the entire ICT sector as a system and understand interdependencies and complex interactions within the system. Second, it allows readers to identify the role played by markets, firms and other institutions in coordinating the activities undertaken within the system. Third, it allows observers to analyse corporate specialisation and corporate strategy and the evolutionary drivers that shape industrial structure in the different layers. The ELM helps to illustrate the role that specific, key companies play in the new ICT ecosystem and to analyse co-evolving demand. Finally, it is also possible to analyse the different levels of profitability in different levels of the system.

There are, however, problems with the depiction of a topographical structure (Fransman 2010). For example, the ELM model fails to show the dynamics of the system including the innovation processes that are a key part of the dynamics. The model is, therefore, not unlike many other frameworks in that it is relatively static (Afuah 2015). More importantly, the model suffers from the same drawbacks as Porter’s Five Forces framework (1980) in that the demarcation between the different layers becomes blurred due to changes in technologies, and therefore, the underlying functionalities. For example, product convergence due to bundling and envelopment (Eisenmann et al. 2006) make it difficult to classify which firms are performing which functions in which layer. Telecoms companies have now become content providers while Internet firms such as Google have also moved into the network operator sector (with Google Fibre) and the network equipment segment (with its handsets). Instead of these being symbiotic relationships they have become disruptive competitive relationships (Downes and Nunes 2013).

Finally, since the model conceptualises the ICT ecosystem as a set of functionalities these become quickly outdated or obsolete (Fransman 2010) and therefore the model needs constantly updating in the current hyper-competitive (D’Aveni 1994) environment. The fact that the current model does not incorporate new developments such as big data and cloud computing is evidence of this drawback. However, Fransman (2010: 1) did state very emphatically that innovation was at the heart of the new ICT ecosystem and that the Internet had become a key and ubiquitous infrastructure that was virtually shaping all economic activity (Fransman 2010: 22).

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