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Mobile Industry Analysis

Autor:   •  October 21, 2017  •  4,635 Words (19 Pages)  •  474 Views

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Due to Big-Bang disruption theory, new disruptive products have a much shorter life cycle and the interval between technology changes becomes shorter and shorter. Two new decisive success factors have emerged, the first mover advantage (The Handset Handbook 2011) and the well-established ecosystem model (Markides and Sosa, 2013).

In the context of high technology-setting industry, the first mover stands a more powerful position in gaining a larger market share and higher profits than following movers. This idea dates back to Schmalensee (1982), who illustrated that it is easier for early entrants in the market to achieve economies of scale and cost efficiencies. It is always much easier to capture the highpoint in the market you have reinvented. In addition, Lieberman and Montgomery (1988) examined that there are three possible sources that the first mover advantages can arise from: technological leadership, preemption of resources and buyers switching costs.

However, the first mover is not without any disadvantages. Several studies suggested that there is no advantage for early entry (VanderWef and Madon, 1997). Markides and Geroski (2005) believes that the early entrants of a new market are almost never the ones that dominate a market. The winners are those who were “lucky” enough to either possess the dominant design at the time of its establishment or jumped into the market when the dominant design was to emerge. Hence, being the first mover is not enough to maintain one’s sustainable competitive advantage. More importantly, they need to undertake a series of actions that turn a niche market into a mass market. Put it simply, they adopt a business model that allows them to grow the mass market and dominate it in the process (Markides and Sosa, 2013).

The traditional theory of disruptive innovation mentioned above, however, is not significant enough to justify Apple's superior performance on its own. The mobile handset market has demonstrated an interesting phenomenon which partly contradicts Christensen's theory. Although smartphone is often referred as a disruptor to the traditional mobile handset market, it does not initially target the low end market nor a new market.

Later on, Koen had provided a new insight with regarding to this phenomenon by considering 3 dimensions of innovation (2011). He suggested that technology, value network and financial hurdle rate are the factors which will limit the capabilities and the willingness of innovation. More importantly, the effect differs between well-established firms and new entrees. With the aid of this theory, it is possible to explain how Apple beats Samsung and Nokia by innovating smart and differently.

In recent years, Apple has been an adamant practitioner in the field of M&A. Bou-Wen Lin and his colleagues pointed out that in high-tech industries, industry leaders are more willing and likely to leverage their market positions and use M&As to further strengthen their market power, while the market challengers are less likely to engage in M&As when locating in technologically crowded areas.

Apart from corporate strategy, other factors such as corporate culture also influence the company’s ability to innovate. According to Jiménez-Jiménez and Sanz-Valle (2011), innovation ability of a firm is highly related to its organizational culture, since empirical evidences showed that organizational culture affects the orientation of either innovation or imitation of a firm.

Sources and methods

The basic methods of research adopted in this dissertation would be literature survey of secondary data. The majority of the journal articles we referred to are initially browsed through university library databases or Warwick WebBridge service. Other company-related information is gathered either through business databases or web news.

Due to the nature of the research topic, the research method of this dissertation is qualitative, which, compared to quantitative research, is more efficient in explaining how and why things happened. Furthermore, the qualitative analysis is further illustrated and supported using graphs and pictures.

The scope of this study is limited to smartphones only, and although function phones are also included in the definition of handset, it is not taken into consideration since it is no longer the mainstream of customer adoption nowadays. For clarity and simplicity reasons, the standard of evaluation of company performance is based on revenue rather than sales or market share, for neither sales nor market share alone can explain the whole story.

This research is not country or region-specific, since all four companies, Apple, Samsung, LG and Nokia are international companies, and their performance in one single region cannot be viewed separately from their overall international strategy.

However, this research is not without limitations. The first one being that financial analysis of these four companies is not taken into consideration. The companies tend to conceal the exact financial data from the public in order to avoid the business secrets leakage and reduce competition. Moreover, since the rate of change in technology is rapid, it is difficult to predict and analyze the data accurately.

Findings and discussion

Big-Bang Disruption

As illustrated in Figure 6 below, the innovation diffusion process goes through four stages, the singularity, the Big-Bang, the Big-Crunch, and entropy. The characteristics that make Big-Bang disruption different from conventional innovation processes are a) the long period of singularity (experimentation); b) the shortness of the exploitation period (Big-Bang itself); and c) the rapid decline afterwards, which can be as steep as the Big-Bang (Denning, 2014).

Our research shows that compared to the traditional bell-shaped innovation diffusion curve, Downes and Nunes’ shark fin-shaped curve provides a more accurate description of the cycle of innovation in smartphone industry, mainly because the bell-shaped curve fails to take into consideration the factors that lead to the ever-shortening product life cycle of the smartphone industry – factors that made the big rise and fall in the curve instead of a more moderate one.

First of all, exponential technology improvements lead to the long period of low-cost experiments and the early entry into the majority phase (Petrick, 2014). On the one hand, companies can conduct low cost experiments, thanks to the continuous improvements of technology, thus competition comes not only from within the industry in the form of well-planned

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