Mobile Industry Analysis

Introduction

In recent years, many technology and electronics companies have initiated and developed their smartphone business. (Table 1)

Table 1 Company Capitalization

Source: Markets.ft.com, (2015). Markets data - stock market, bond, equity, commodity prices - FT.com. [online] Available at: http://markets.ft.com [Accessed 27 May 2015].

It is easy to judge corporate performance simply from the financial figures alone. However, the scale of operation is no longer the most significant factor anymore, especially after Nokia failed to stay in the game from 2013 and Apple exceeded Samsung on revenue and became the world’s largest smartphone maker. After Apple’s launch of its revolutionized iPhone in 2007, which set a new milestone in the handset history, the rules of thumb in the mobile phone market have been profoundly changed.

The essay begins with the introduction of the handset industry and the four companies, followed by literature reviews and sources and methods of research. Then come the findings and discussions, and the conclusion.

The thesis statement of this dissertation is that corporate strategy is the reason why Apple, as a relatively new player in the handset market, is more innovative than other competitors and eventually outperforms the majority of the players in the industry.

Literature review

Due to the characteristics of ever-shortening product life cycle in smartphone industry, the ability to innovate has become the most important success factor for companies competing in this sector.

Traditional theories on diffusion of innovation are represented by Everett Rogers’ classic bell-shaped adoption curve. In his book (Rogers, 2003), he pointed out that adopters should be divided into five categories according to their innovativeness – innovators, early adopters, early majority, late majority and laggards. The distribution is represented by the percentage of the adopters, and for every successful innovation, the curve should form a bell shape. (Figure 1)

[pic 1]

Figure 1 Innovation Curve

Source: http://www.fashionverbatim.com/20061010/everett-rogers-diffusion-of/

However, the research on innovation in handset industry shows a different result (Figure 2). Denning suggested that the wave of the so-called “Big-Bang disruption”, which is similar to disruptive innovation, will eventually affect all industries and is currently particularly obvious in mobile and other digital industries (Denning, 2014). Larry Downes and Paul F. Nunes further suggested that Big-Bang disruption does not fit Rogers’ model of innovation adoption, for it has a much shorter adoption period, with a steeper and more compressed curve of customer adoption (Downes and Nunes, 2013). They believed that the Big-Bang disruption occurs in four stages – singularity, Big-Bang, Big-Crunch, and entropy.

[pic 2]

Figure 2 Traditional Technology Adoption vs. Big-Bang Disruption

Source: Downes, L. and Nunes, P. (2013). Big-Bang Disruption. Harvard Business Review, [online] 91(3), pp.44-56.

Different understandings of the technology diffusion pattern would lead to fundamentally different corporate strategies. Thus the further study into this field is needed to explain the different performance of those four companies.

As shown below, Clayton Christensen developed the traditional theory of disruptive innovation in the late 90s. He suggested that the dominant incumbent firms in the market often fail to keep out new entrants, as they enter the market from the bottom and move they way up until eventually overtake the established firms. He also defined that disruptive innovation is often "simpler, cheaper" or provided for previously un-served customers (1997). (Figure 3)

According to Christensen, the dotted lines are the customer’s level of satisfaction of the phones, which slowly increase over time. The bell curve shows the reality of the product. On the highest tier, the customer may never be satisfied with the best product available and the lowest tier can be overly satisfied with low product performance. So on the average, the dotted line indicating that the product is good enough to serve the existing customers.

The bold lines then indicate the innovations from the companies. The speed of the company’s innovation needs to be faster than the rising speed of customer satisfaction level, so companies make continuous innovation by gathering feedback from customers, as represented by the curved-dotted lines. The bold lines will then move higher and eventually exceed the customer satisfaction, leading to an increase in demand and customers’ willingness to pay at higher prices.

Contrary to continuous innovation, disruptive innovations do not bring better products to the market, but introduce a simpler and convenient new product to the market instead. Wienand  (2006) mentioned that disruptive products do not become viable for all customers until it exceeds customer satisfaction line. However, if it exceeds the line, it will then gain customers from the old products, killing the old product industry leader and creating the new one. The customer satisfaction will then change and the customer will stop using the old product. Making the rest of the improvement of the old product became redundant, causing the companies to spend wastefully. (Figure 4)

In order to avoid the innovation gap that causes a downfall in revenue, companies often start the next technology while they are still gaining the revenue from their current products. At first the line of S-curve is not steep, because the demand is still little as they are in the innovators and early adopters period. This means that they tend to have lower volume and higher cost as appeared in the economy of scale graph on the right. The cost of manufacturing will then decrease as the volume is gained. (Figure 5)