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Porter’s Five Forces Framework (1980)
Michael Porter continues to be identified as the leading exponent of the ‘market positioning’ school of strategy, basing his views on industrial organisation economics (IOE). Porter (1980: 3) argues that it is still critical to understand the position of the firm within its industry since the industry structure has a strong influence on determining the competitive rules of the game, as well as the strategies that are potentially available to the firm. This philosophy underpins the SCP model of strategy (Mason 1949; Bain 1956) that was discussed in Chapter 1.
Porter still argues that the economic structure of an industry is a product of five forces whose collective strength determines the ‘ultimate profit potential in the industry’ (Porter 1980: 3). This means that an organisation’s ability to manage these forces - to overcome weaknesses with respect to these forces or to take advantage of opportunities offered by the alignment of these forces - determines the attractiveness of the industry and the organisation’s ability to return a profitable performance. This approach was endorsed by Schmalansee (1985) whose research revealed significant industry differences in performance that accounted for over 75 percent average returns based on US industry data dating from 1975.
Despite the widespread adoption of Porter’s Five Forces framework (1980), the Five Forces model and Porter’s positioning school have been subjected to a significant amount of criticism over recent years (Rumelt 1991; Hawawini et al. 2003; McNamara et al. 2005). For example, Rumelt’s (1991) research drew completely different conclusions to Schmalansee’s (1985) earlier work. Rumelt discovered that business-specific rather than industry-specific factors were responsible for high corporate performance. This is a view that is supported in later chapters of the book where innovation, second-order competences and Schumpeterian rents (Schumpeter 1942: Danneels 2012) are seen as key drivers of financial success and not industry-effects.
These criticisms will now be analysed in more detail since they are highly relevant to the information and communications technology (ICT) sector. Jay Barney (1991) criticised Porter’s Five Forces model based on four important criteria which included resource-based criticisms, dynamic criticisms, practice-based criticisms and sector-based criticisms.
Resource-based criticisms: According to Barney’s (1991) resource-based criticism, Porter (1980) made two major assumptions. First, he assumed that organisations within an industry were identical in terms of their strategic resources and the strategies they pursued. The second assumption was that if there was any resource heterogeneity, then this would be short-lived. For example, if a new entrant arrived or an incumbent developed new and valuable resources then the resources tended to be imitable or mobile, and hence the advantages they brought would only be temporary.
According to Barney (1991) and the RBV developed during the 1990s, resource heterogeneity and not resource homogeneity exists between organisations, and there is no inevitability that it will disappear along with any advantage that heterogeneity brings. Since the RBV considers competitive advantage to be a product of superior resources and capabilities there are times when an organisation’s resources and capabilities are so superior that competitive advantage becomes sustainable over the longer term. This is what is known as a Ricardian rent (Grant 2016) rather than a monopoly rent that characterises Porter’s (1979; Porter 1980) positioning school.
Barney’s criticism of Porter’s first assumption that organisations within an industry were not identical in terms of the resources and strategies they adopted is highly appropriate with regards to the ICT sector. The ICT sector is highly diverse, consisting of an ecosystem of companies responsible for telecoms and Internet infrastructure, computer hardware and software plus the actual Internet-based firms, chip makers and media (content) companies, etc. Even if you break the sector down into individual technology clusters (Porter 1998; 2001) you will still find significant levels of diversity within each cluster.
Business model innovation (Afuah 2004) plus new and diverse strategies and ways of creating value within the ICT sector have been one of the biggest changes in the last five years. If you compare the leading ICT technology companies across North America and Asia it is noticeable that they are pursuing very different strategic approaches. The leading US Internet-based firms or ‘Gang of Four’ (Amazon, Apple, Google, and Facebook) each have a different set of strategies. This diversity increases when they are compared to the Chinese Internet-based firms, the BAT (Baidu, Alibaba, and Tencent). Corporate strategies differ based on the core services provided which vary from search, ecommerce and social networking to handset production and content. Competitive strategies also vary in terms of how the platforms are monetised and whether they are open source (Google) or relatively closed and proprietary (as in Apple’s case). Although there are signs of technological convergence within the ICT sector, there is still massive diversity both across the sector and within individual technology clusters (Porter 1998) This is largely due to the continuous innovation taking place.
There is also resource heterogeneity between ICT companies and the brick-and-mortar firms that they are disrupting. Amazon’s resource-base is completely different to a brick-and-mortar bookstore or a big-box retailer such as Walmart. Apple also has a different resource configuration to a traditional record company. The new emerging app-based aggregator firms in financial technology (Fintech) have different resources to the Banks, and Uber and Airbnb have different resources to traditional transport and hotel providers. Resources within the ICT sector are also heterogeneous. Data is a key resource in the ICT sector, and the capability to store, process and create information and intelligence is a core competency (Prahalad and Hamel 1990). However, the data resources of Google and Facebook and their Big Data capabilities have not been imitated by other members of the ICT ecosystem such as the telecoms operators who are not as ‘data rich’. There are subsequently significant variations between the data and information resources and capabilities within the ICT sector with Internet platforms gaining an advantage over established incumbents such as Hewlett-Packard and IBM. It will also become apparent when analysing the organisms within the hydrothermal vent ecosystem model in Chapter 5, that the main species (the tube worms, vent mussels and giant clams) are also highly differentiated and specialised (Van Dover 2000).
Although the longevity of competitive advantage has shortened considerably (McGrath 2013) within the modern ICT sector and the speed of imitation has increased due to hyper-competition (D’Aveni 1994), there are exceptions to the rule. For example, where a company achieves platform leadership (Gawer and Cusumano 2002) or becomes a keystone player (Iansiti and Levien 2004) within a technology ecosystem, then the firm(s) concerned enjoy a sustained advantage. Microsoft and Intel’s domination of the PC industry, Amazon’s strong position in e-commerce, Google’s domination of search, Facebook’s pervasiveness in social networking and Apple’s strong position in mobile computing are all examples of companies whose resource advantages have not been eroded quickly through imitation. Where a new technology platform is emerging and/or a ‘standards war’ is being played out then ‘winner-takes- all’ (Eisenmann et al. 2006) and network-effects (Parker and Alstyne 2005) usually ensure that the successful firm(s) end up with a more robust advantage that is not eroded quickly.
Dynamic Criticisms: another criticism of Porter’s Five Forces framework (Porter 1980) is its lack of dynamism and the fact that it is a static model in a highly volatile environment. This problem is magnified in high innovation sectors such as ICT where there is continuous innovation, high levels of disequilibrium and no tangible status quo (D’Aveni 1994; McGrath 2013). The model, therefore, has only limited usefulness since it is largely a snapshot at a single point in time.
Defining industry boundaries has also become a problem since these have either become blurred by technology or rendered irrelevant. Industry convergence has been one of the biggest trends in recent years due to the rise of digital internet platforms and ecosystems. For example, drawing an industry boundary for a smartphone is both superfluous and irrelevant since it involves multiple industries such as telecommunications, computing, consumer electronics and media content. This is the very essence of the modern ICT ecosystem which is industry agnostic (Teece 2012). Platform-based Internet companies such as the North American ‘Gang of Four’ (Amazon, Apple, Google and Facebook) and the Chinese ‘BAT’ (Baidu, Alibaba and Tencent), all operate across industries and deliver products and services using multi-sided platform models (Hagiu 2014).
David Teece (2012) suggested that Porter’s original Five Forces framework failed to recognise the effect of rapid innovation on industry boundaries and that this undermined the value of its application. Robert Grant (2016) also suggested that the Five Forces model failed to acknowledge the complexity of relationships between organisations and recommended the addition of a new sixth force - the ‘complementer’. The purpose of the sixth force was to highlight that an organisation is often so interconnected with other organisations that they may have merged value chains (Wirtz 2001). Excluding ‘complementers’ therefore risked underestimating their importance. ‘Complementers’ is a concept borrowed from ecosystem theory (Yoffie and Kwak 2006) which represents niche players who populate the periphery of an ecosystem and provide critical inputs in the form of products or services. In the ICT ecosystem, app developers and the Apple and Google app stores are important complementors that help to create important network effects for their respective hardware products and online search platforms. A complementor (Brandenburger and Nalebuff 1996) is, therefore, more than a simple supplier since they are co-creators of an organisation’s ultimate product or service. Ecosystem and platform theories will be analysed in more detail in Chapter 4.
Practice-based criticisms: another criticism of Porter’s (1980) framework is the tendency to group various agents together (buyers, suppliers, and competitors). There are not only high levels of heterogeneity between these participants, but there may also be some form of co-opetition taking place (Brandenburger and Nalebuff 1996). For example, in the telecoms segment of the ICT sector, a virtual network operator (VNO) may pay a fee to an incumbent owner of a fixed line network. This means that the VNO is both a competitor to the incumbent network owner and also its customer. Virgin Media is, therefore, a competitor and a customer of BT in the UK. Samsung Electronics not only supplies D-Ram chips for the Apple iPhone but it also competes against Apple with its own smartphone devices. This makes the model highly complex when analysing a high technology ecosystem such as ICT where there are strong symbiotic relationships and mutualism (where firms cannot survive without each other) and the co-creation of products and services (Moore 1996; Fransman 2010). The linear and one-dimensional nature of Porter’s model is, therefore, highlighted and the need for a multi-dimensional perspective.
Brandenburger and Nalebuff’s (1996) theory of co-opetition was based upon the Value Net model and used game theory to describe four player classifications which included customers, suppliers, competitors and com- plementors. They suggested that the Value Net should be used to create added value for consumers by bundling complementary products. Feldman (2002) recognised that bundling had gained significant momentum in the mobile technologies industry. For example, mobile phones were no longer used for voice-to-voice communication. New features were added including SMS, ring tones, photo messaging, video messaging, music downloads, directory assistance and Internet access, etc. This was a very different perspective to Michael Porter’s with powerful alignment to ICT ecosystem thinking.
Sector-based criticisms: are also relevant since it is important to recall the actual origins of Porter’s model. The thinking behind the Five Forces framework dates back to the 1950s and Edward Mason (1949) and Joe Bain’s (1956) SCP model that provided a framework within which further propositions concerning the relationship between strategy and firm performance could be developed. Porter’s research, meanwhile, was overwhelmingly based on American organisations from the manufacturing sector. The model was also developed at the end of the 1970s when the industry boundaries were clear and distinct and had not been blurred or made obsolete by digitisation and Internet-based technology firms. Although the model did acknowledge the convergence of industries such as telecommunications and computing (ICT), it did not anticipate how far this would go. Porter’s Five Forces model does not, therefore, provide a very useful or up-to-date tool for analysing the modern ICT sector and does, in fact, highlight a number of shortcomings. Trying to foresee competitor threats based on industry boundaries that are vague and blurred or irrelevant is likely to lead to firms becoming blind-sided and myopic. For example, during the battle for the PC industry standard during the 1980s, the biggest threat to Apple wasn’t coming from their direct industry rivals such as Dell, Compaq and IBM but from the suppliers of the micro-processor chips and software, Intel and Microsoft. More recently, the threat to Microsoft’s PC-based platform model did not come from other PC hardware or software products but from a smartphone, tablet, and a new mobile platform. In such circumstances, Porter’s Five Forces model is likely to be a hindrance rather than help and thereby result in false signals being disseminated (Downes 1997).
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