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Technology Change, Economic Feasibility and Creative Destruction:

The Case of New Electronic Products and Services

By

Jeffrey L Funk

Forthcoming

INDUSTRIAL AND CORPORATE CHANGE

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Technology Change, Economic Feasibility and Creative Destruction:

The Case of New Electronic Products and Services

Abstract

This paper shows how new forms of electronic products and services become economically

feasible and thus candidates for commercialization and creative destruction as improvements in

standard electronic components such as microprocessors, memory, and displays occur. Unlike the

predominant viewpoint in which commercialization is reached as advances in science facilitate

design changes that enable improvements in performance and cost, most new forms of electronic

products and services are not invented in a scientific sense and the cost and performance of them

are primarily driven by improvements in standard components. They become candidates for

commercialization as the cost and performance of standard components reach the levels necessary

for the final products and services to have the required levels of performance and cost. This

suggests that when managers, policy makers, engineers, and entrepreneurs consider the choice and

timing of commercializing new electronic products and services, they should understand the

composition of new technologies, the impact of components on a technology’s cost, performance

and design, and the rates of improvement in the components.

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1. Introduction

Although different terms are used, most economic (Schumpeter, 1934; Rosenberg, 1974,

1982, 1994; Acemoglu and Robinson, 2012), marketing (Chandy and Tellis, 1998), and

management (Christensen, 1997; Adner, 2002) scholars agree that creative destruction is an

essential part of economic and firm growth. Technologies such as steam engines, electricity,

automobiles, aircraft, integrated circuits, computers, and the Internet destroyed an existing order

of firms and created a new one in the form of new products, services, and systems. These new

forms of products, services, and systems, have enabled dramatic improvements in economic

productivity (Solow, 1957) and thus living standards and have created winners and losers at the

individual, firm, and country level (Acemoglu and Robinson, 2012).

But how should firms, entrepreneurs, governments, and universities search for these new

technologies? Where should they look, what should they monitor, and how can managers and

policy makers use this information to “look forward and reason back,” in order to identify

commercially viable technologies and develop good strategies for them (Yoffie and Cusumano,

2015)? These questions suggest a more fundamental question: what is the long-term evolutionary

process (Nelson and Winter, 1982; Ziman, 2000; Murmann, 2004) by which new technologies

become economically feasible and thus candidates for commercialization and creative

destruction? There may be multiple processes depending on a technology’s paradigm (Dosi, 1982)

and thus different types of technologies may have different directions and rates of change, types

of problems to solve, and ways of achieving improvements (Dosi, 1982; Dosi and Nelson, 2010).

The predominant viewpoint is that new technologies proceed through distinct stages of

invention (Arthur, 2007), commercialization, and diffusion (Rogers, 1963) in which advances in

science facilitate design changes that enable improvements in performance and cost (Rosenberg,

1974, 1982, 1994; Balconi et al, 2012). Advances in science – new explanations of natural or

artificial phenomena - play an important role in this process because they facilitate the new product

and process designs that lead to improvements along cost and performance trajectories (Dosi,

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1982) over the many decades before commercialization occurs (Rosenberg, 1974; Arthur, 2009;

Balconi et al, 2012; Funk and Magee, 2015). Following commercialization and implementation

(Geels, 2002, 2004; Ansari and Garud, 2008), costs continue to fall as diffusion occurs, production

is expanded, and R&D is increased, thus leading to improvements in performance and cost along

an experience curve (Dutton and Thomas, 1984; Lieberman, 1984; Balasubramania and

Lieberman, 2010).

This paper considers important types of products and services for which an alternative process

is more appropriate than is the predominant viewpoint of invention, commercialization, and

diffusion. Most new forms of computers, smart phones and apps, game consoles and content,

Internet services and content, wearable computing, and other electronic products and services,

even when they are considered radical innovations that lead to creative destruction, do not directly

involve advances in science in their overall designs and thus they are not invented in a scientific

sense. Second, anecdotal evidence (Dedrick et al, 2009; Funk, 2013a) suggests that the cost of

most electronic products and services are impacted more by standard components such as

microprocessors, memory, and displays than by assembly costs and thus cumulative production

and experience curves are not useful for analyzing their cost and performance. Third, many of

these standard components have experienced very rapid rates of improvements of greater than

30% per year over the last 50 years (Funk and Magee, 2015).

This paper proceeds as follows. It first surveys the literature on how new technologies

become economically feasible and thus become candidates for commercialization and creative

destruction. Second, the methods of finding and analyzing cost data and characterizing the

improvements in performance and cost of products are summarized. Third, it shows that the costs

of most electronic products primarily depend on the cost of standard components such as

microprocessors, memory, and displays. Fourth, it analyzes two recently introduced electronic

products, the iPhone and the iPad, that have led to creative destructions in hardware and app-based

services. Fifth, using longitudinal data on the iPhone, iPad and their components, it works

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backwards to understand the process by which they and their associated services became

economically feasible. Sixth, it uses this analysis to propose an evolutionary process by which

electronic products and services become economically feasible.

2. Literature Review

New technologies must provide certain levels of performance and price before they will

become economically feasible and thus candidates for commercialization. This can be graphically

represented with demand and supply curves in Figure 1. For simplification, this figure focuses on

the typical movements of a supply curve over time as a new technology becomes cheaper. In

particular, the price (and thus the cost) of a new technology must fall below a maximum threshold

of price before users will consider purchasing products based on the new technology (see the

arrow in Figure 1). If performance instead of price is plotted on the y-axis, one can also represent

minimum thresholds of performance in Figure 1; the performance of a new technology must

exceed this performance before users will consider purchasing products based on the new

technology (Green and Wind, 1973; Lancaster, 1979; Adner, 2002, 2004; Adner and Zemsky,

2005). Since multiple dimensions of performance are typically relevant for a new technology,

multiple figures can also be used or the multiple dimensions can be combined into a single value

proposition (Chandy and Tellis, 1998), which should be superior to the one for the previous

technology. One can also define minimum levels of performance and maximum levels of price for

each user represented by the demand curve in Figure 1 where each user may have different needs

and willingness to pay partly because they are using the technology for different applications.

But how does a technology reach the point at which performance exceeds the minimum

threshold of performance and at which price falls below the maximum threshold of price for the

early users represented by the demand curve in Figure 1? Answering these questions requires an

understanding of technology paradigms (Dosi, 1982) including the directions and rates of change,

the problems being solved, and the way improvements are being achieved (Dosi, 1982: Dosi and

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Nelson, 2010). More generally speaking, what is the long-term evolutionary process (Nelson and

Winter, 1982; Ziman, 2000; Murmann, 2004) by which this occurs, and how can managers (and

policy makers) use this information to “look forward and reason back” (Yoffie and Cusumano,

2015) in order to develop good strategies for new technologies, including the timing of the

commercialization.

As noted in the introduction, the predominant viewpoint is that improvements occur as new

technologies proceed through distinct stages of invention (Arthur, 2007), commercialization, and

diffusion (Rogers, 1963) in which advances in science facilitate improvements in the overall

design (Rosenberg, 1974; Arthur, 2009; Balconi et al, 2012), particularly before

commercialization. For example, the creation of new materials that better exploited physical

phenomena (Funk, 2013b) enabled rapid improvements over many decades in the performance

and cost of quantum dot solar cells and displays; organic transistors, solar cells, and displays; and

of quantum computers. Also before commercialization, reductions in the scale of transistors and

memory cells enabled rapid improvements in superconducting Josephson junctions and resistive

RAM (Funk and Magee, 2015). Consistent with other research (Rosenberg, 1974; Dosi, 1982;

Arthur, 2009; Balconi et al, 2012), advances in science facilitated the use of new materials and the

reductions in scale (Funk and Magee, 2015).

The creation and demonstration (i.e., invention) of new concepts is also sometimes facilitated

by advances in science. This is because a new explanation of physical or artificial phenomenon

often forms the basis for a new concept (Arthur, 2007, 2009), sometimes through combinatorial

search and recursion (Fleming, 2001; Fleming and Sorenson, 2001; Arthur, 2007). Thus, although

some old technologies (e.g., the steam engine) were commercialized before most advances in

science occurred, the concepts for more recent technologies were mostly based on advances in

science. In addition to the examples mentioned in the previous paragraph, other examples include

radio (Lewis, 1991), television (Bilby, 1986), semiconductors (Tilton, 1971), lasers, light-emitting

diodes (Orton, 2005); and liquid crystal displays (Castellano, 2005).

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After a technology is commercialized and implementation problems are solved (Geels, 2002,

2004; Ansari and Garud, 2008), the predominant viewpoint is that another set of dynamics begins

to operate; costs fall as learning is done in factories (Wright 1936; Argote and Epple 1990) and as

R&D spending is increased (Schmookler, 1966; Sinclair et al, 2000). The former is called the

learning curve (Arrow 1962; Thornton and Thompson, 2001) and the latter is called the experience

curve. In the latter, some argue that all of the cost and performance improvements can be explained

in a model linking cumulative production with the improvements (Dutton and Thomas, 1984;

Lieberman, 1984; Balasubramania and Lieberman, 2010) in which changes in the product design

are defined as novel combinations of components (Basalla, 1995; Iansiti, 1995).

Consider automobiles. Improvements in the acceleration of automobiles, the comfort and

safety of the ride, the aesthetics of the interior and exterior, and the durability of the automobile

came from novel combinations of mechanical components at the system level over many decades

(Abernathy and Clark, 1985). These novel designs largely involve unique rather than standard

components. For example, one comprehensive study of 29 new automobile products found that

standard components only represented about 6% of the material costs (Clark and Fujimoto, 1991).

The argument linking cumulative production with improvements in performance and/or cost

is also implicit in Christensen’s (1997) analyses of hard disk drives, computers and other

“disruptive” technologies. Although he plots performance vs. time (and not cumulative

production), his models imply that the introduction and production of a low-end product leads to

increases in R&D spending, the increased R&D spending purportedly leads to rapid improvements

in the low-end product, and these rapid improvements cause the new product to replace the

dominant product.

The literature on general-purpose technologies (David, 1990; Bresnahan and Trajtenberg,

1995; Helpman, 2003; Lipsey et al, 2005; Jovanovic and Rousseau, 2005) suggests an alternative

long-term evolutionary process (Nelson and Winter, 1982; Ziman, 2000; Murmann, 2004) by

which new technologies become economically feasible and thus candidates for commercialization

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and creative destruction. Many of the recently defined GPTs are electronic components or

electronic products/systems. Examples of the former include integrated circuits (ICs) and lasers

and examples of the latter include computers and the Internet (David, 1990; Bresnahan and

Trajtenberg, 1995; Helpman, 2003; Lipsey et al, 2005). Building from the concept of a GPT, some

papers and books have analyzed the relationship between computers (Nordhaus, 2007), telecom,

the productivity of higher-level systems (Cortada, 2003, 2005), and economic growth (Oliner and

Sichel, 2002; Olner, Sichel and Stiroh, 2007; Jorgensen et al, 2008) where it is recognized that

improvements in standard ICs are the sources of the improvement in computers by computer

scientists (Smith, 1989), economists (Bresnahan and Trajtenberg, 1995), and management

scholars (Baldwin and Clark, 2000; Funk, 2013a, Funk, 2013b). The large impact of ICs on the

performance and cost of electronic products and services suggests these electronic products have

a different type of technology paradigm (Dosi, 1982) than do other products and services.

One reason these ICs and other electronic components are defined as GPTs is because they

have experienced rapid improvements over many decades. For example, the number of transistors

per chip for microprocessors and other ICs, the number of memory bits per dynamic random

access memory (DRAMs) and flash memory, and the number of pixels per camera chip have

doubled every 18 to 24 months for many years, resulting in relatively constant annual rates of

improvement of 30% to 40% per year (Funk and Magee, 2015). Often called Moore’s Law, these

improvements are linked by a common set of product and process design changes that are

facilitated by advances in science. As described in the semiconductor industry’s annual report

(International Technology Roadmap for Semiconductors), there is a common trajectory for many

of these ICs in which reductions in the feature size of transistors, memory cells, and pixels enable

increases in the number of transistors, memory bits, or pixels per chip respectively (ITRS, many

years); this forms the basis for the technology paradigm of ICs (Funk, 2013a).

In summary, these rapid rates of improvements in ICs and other standard electronic

components and the literature on GPTs suggest that some technologies become economically

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feasible and candidates for commercialization through a long-term evolutionary process (Nelson

and Winter, 1982; Ziman, 2000; Murmann, 2004) that is very different from the predominant

viewpoint of invention, commercialization, and diffusion. The purpose of this paper is to analyze

this long-term process. Can we better understand the levels of performance and cost that are

needed in these components before new types of electronic products and services become

economically feasible? What other factors might impact on these required levels? How can

decision makers use knowledge of these factors and the overall process of technology change to

better search for new types of electronic products and services and commercialize them?

3. Methodology

The first step was to find detailed cost data on electronic products. Such data were found from

iSuppli and TechInsights on 89 products that can be classified as smart phones, tablet computers,

eBook readers, game consoles, MP3 players, large-screen televisions, Internet TVs, and Google

Glasses, for the years 2007 to 2014. Although cost data for other electronic products such as digital

cameras, drones, scanners, 3D printers, and smart watches were also investigated, data in

sufficient detail were not found. For the data that was found, iSuppli and TechInsights publish cost

data, some for clients and some for the public, and the public data includes cost data in various

levels of tabular detail. Some tables provide final assembly costs in addition to the cost of materials,

some tables provide more details on materials than do other tables, and one table provided data on

licensing costs (5% of the first iPhone). Most of the tables often provide information on the name

of the component and the identity of the suppliers in addition to the cost data and component

details. All of the tables also include one or multiple “others” categories in which inexpensive

components are lumped together. It is assumed that each line item (component and final assembly)

also include the cost of logistics, production tooling, and inventory. It is also assumed that the

costs are similar across customers of these standard components, although large customers will

obtain standard components both sooner and for less cost than will other customers.

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Second, once the data was collected and placed in an excel spreadsheet, components were

defined as standard or non-standard components. Although some scholars might define standard

components as ones with standard interfaces, this paper is more concerned with cost dynamics

than with modular design/vertical disintegration and thus standard components are defined as

components that are used by multiple suppliers of an end-product and/or by multiple end products

from a single supplier. It should be noted that vertical disintegration (Baldwin and Clark, 2000) is

considered a separate (and important) research topic from the one being addressed in this paper.

To better explain the definition of standard components used in this paper, Table 1 shows the

typical data that is available for electronic products, in this case Apple’s iPhone5s. It shows the

costs for 11 categories of materials and for assembly and total cost. It also shows the specifications

for 9 different components, all of which are designed (except for the A7 processor) and

manufactured by firms other than Apple. All of these components are used in other phones or in

the cases of the A7 processor and touch screen, are used in other Apple products such as iPods

and tablet computers. Since the touch screen was unique to the iPhone until the iPad was released

in April 2010, the touch screen and its associated circuity (e.g., touch screen controller) are defined

as non-standard components in the first-generation iPhone and the iPhone 3 but are defined as

standard components in the iPhone5s (See Table 1) and subsequent iPhones. It is important to

recognize that the use of touch screen technologies in the iPhone and other smart phones (very

similar technologies are used) have made touch screen technology a standard component that is

available in a wide variety of electronic products.

Thus, except for the mechanical, electro-mechanical, and box contents, all of the components

in Table 1 can be defined as standard components and thus provide a lower estimate for the cost

of standard components in the Apple iPhone 5s. It is a lower estimate because some of the

mechanical and electro-mechanical components might also be standard components. For example,

in the more detailed cost breakdowns that are available for some of the other products, cost data

is available for passive electronic components such as filters that are used by many phone suppliers.

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However, these passive components are placed in the “electro-mechanical” or “other” category

for many of the products by iSuppli and TechInsights and thus it is difficult to distinguish between

standard passive components and other components that are unique to the product. This causes

this paper’s analysis to underestimate the contribution of standard components to costs.

The third step in this paper’s analysis was to place the standard components into multiple

categories. The information from iSuppli and TechInsight provided various levels of detail on the

components, their category, and their specifications. These categories were used to identify a set

of component categories that are common to most or all of the nine product types for which data

was collected. For example, returning to Table 1 and beginning with NAND flash and DRAM,

they are defined as one category of memory. This process was repeated for each of the items in

Table 1 and the other 88 products. This process also relied on the author’s knowledge of electronic

components and products both as an engineer early in his career and as a researcher and consultant

on these products over the last 20 years.

Fourth, detailed information were collected on the evolution over time in the iPhone and iPad,

both of which have led to creative destruction in both hardware and app-based services. Both are

radical innovations since they involve large changes in both the concepts and architectures. The

concept of smart phones involves browsing and apps while previous phones involved voice and

texting (Yoffie and Kim, 2010; West and Mace, 2010). The concept of tablet computers involves

touch screen browsing while previous computers involve mouse-based browsing.

Data were collected on the performance measures and how improvements in these measures

are characterized. Which measures of performance are measured and improved? What types of

design changes enabled these improvements and how are they different from the design changes

that enabled improvements in other products such as automobiles (Abernathy and Clark, 1985)?

Apple’s home pages and other sites were investigated and it was found that Wikipedia’s pages on

the iPhone and iPad (probably managed by Apple or by an Apple supporter) are consistent with

Apple’s home pages and provide a good summary of how these products were improved.

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Fifth, the information on the evolution of the iPhone and iPad were used to better understand

how they first emerged by working backwards in time. As we go back in time, the performance of

the end products and components becomes lower while the prices typically become higher.

Building from others (Green and Wind, 1973; Lancaster, 1979; Funk, 2009, 2013a), what was the

cost/price and performance in both the end product and the components that were needed before

these end products become economically feasible? Since an eco-system of apps are considered an

important part of the iPhone’s success, business model, and strategy (Yoffie and Kim, 2010), what

was the cost/price and performance that was needed in the components before Apple’s app-based

strategy became economically feasible? This also enables us to better understand how and when

specific apps, i.e., new electronic services, became economically feasible, many of which have

valuations greater than $1 billion and as high as $50 billion (e.g., Uber) and thus may lead to

creative destruction (WSJ, 2015). The next section presents the results beginning with the “first

step” discussed above, which is to understand the cost breakdown of electronic products.

4. Results

Table 2 summarizes the average percentage cost representation of final assembly and of

standard components for nine products. This data demonstrates that final assembly represents a

small percentage of costs and that standard components represents a much larger percentage of

costs than does final assembly. Final assembly represents less than 6% of total costs for all of the

nine product types and it is less than 3% for laptop computers, game consoles, televisions, and

Google Glasses. Standard components represent more than 55% of total cost and more than 60%

of material costs for all nine product types. They represent more than 80% of total costs and total

material costs for smart phones, tablet computers, eBook Readers, and televisions.

Some readers might argue that assembly operations once constituted a large percentage of

total costs but that learning in these assembly operations has reduced assembly’s contribution for

total costs to their current low values. Although this might be true for products first introduced

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decades ago such as laptop computers, game consoles, and small-screen televisions, it is not true

for the newer products in Table 2. Apple’s first iPhone is usually defined as the first successful

Internet-compatible smart phone outside of Japan and Korea and it was introduced in 2007. Tablet

computers and eBook Readers were first introduced in about 2008, large-screen televisions were

introduced a few years earlier, and Internet TVs and Google Glass were introduced much more

recently. The recent introduction of these product types and the fact that the data in Table 2 covers

2007 to 2014 suggest that assembly costs have always represented a small percentage of total costs

and that standard components have always represented a large percentage of total costs.

Table 3 probes deeper. It summarizes the average cost contribution of specific standard

component categories for the nine types of products. All of these categories are mentioned by

iSuppli and TechInsights in their cost breakdowns and this table merely combines some categories

into larger categories. An entry of “None” means that the component is not used in the product

and an entry of “Not Available” means that the component is used in the product but that the data

is not available.

Looking at Table 3 in more detail, we begin with memory and move to the right. SRAM (Static

Random Access Memory), DRAM (Dynamic RAM), and flash memory are used in most or all of

the nine types of products to store audio, graphics, video, and other data while hard disks are used

in just a few products. Microprocessors are used in all of the products to process audio and video

signals. Processors and memory represent the largest percentages of costs in game consoles (77%)

followed by Internet TVs (47%) and smart phones (37%). For smart phones, two different

processors, one for internal processing of music, video, and other applications and one for

interacting with the cellular network, have been used for many years but they have been integrated

into a single chip in some cases (ISCC, 2013). The bills of materials from iSuppli and TechInsight

suggest that more than 90% of smart phones use one of six standard processors from five suppliers

(Travlos, 2012; Peddie, 2014; Kondojjala, 2012), most of which are based on ARM cores.

Displays are used in all of the products except game consoles and Internet TV and displays

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represent the largest percentage of costs in large screen televisions (76%) followed by tablet

computers (38%) and eBook Readers (42%). Power management modules are in all of the

products and batteries are in all of the products except game consoles and televisions but they

represent a small percentage of final costs in all the products. Cameras are in about half the

products as are connectivity and sensors. The category of “connectivity and sensors” includes a

large variety of standard components that do WiFi, FM radio, GPS, and Bluetooth; these functions

have been integrated into a single chip by many suppliers. Sensors include accelerometers,

gyroscopes and compasses, among others.

The data in Table 3 suggest that a small number of standard components constitute most of the

final cost and thus probably determine the performance of the final products. Economists would

probably call many of the components in Table 3, particularly memory, microprocessors, and

displays, general-purpose technologies. To investigate the effect of standard components on how

and when new forms of electronic products and services become economically feasible, the

evolution of the iPhone and iPad, including smart phone apps are investigated in more detail.

4.1 Smart Phones

Table 4 summarizes the evolution of the iPhone. The first iPhone was introduced in 2007 and

it is a radical innovation since it involved large changes in both the concept and architecture, as

noted above. The concept of smart phones involves browsing and apps while previous phones

involved voice and texting (Yoffie and Kim, 2010). The architecture for the iPhone was also new

and can be defined as a loosely coupled architecture (Yoo et al, 2010). Many of the subsequent

iPhones can also be defined as architectural innovations (Henderson and Clark, 1990), albeit

smaller ones than the first iPhone, because functions were combined into fewer chips, electronic

and mechanical parts were moved around to meet form factor goals, and software was reorganized

to enhance usability and performance.

Table 4 organizes the evolution of the iPhone by component type since this is the way Apple

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and others characterize the improvements. New versions of the iPhone have more memory, faster

and better processors, higher resolution displays and cameras, faster and higher resolution video

cameras, faster WiFi, and Bluetooth, and new features such as compasses, gyroscopes, voice

recognition, finger-print scanners, and near field communication. More memory increases the

number of songs, pictures, videos, games, and apps that can be stored in a phone. Faster

application and graphics processors enable increased sophistication of applications and of video

and game processing and these faster processors are needed to handle higher resolution displays

and cameras, more sophisticated games and apps, and higher audio and video resolutions (ISSCC,

2013). Newer and faster cellular processors enable compatibility with newer cellular standards

such as 3G and 4G that have faster data speeds (Gonzalez, 2010). The faster and newer WiFi and

Bluetooth chips also enable faster data speeds through compatibility with newer standards (WiFi,

2015) for these technologies. New forms of standard components such as compasses, gyroscopes,

voice recognition, finger-print scanners, and near field communication also provide new features.

The one component in Table 4 that does not show significant improvements is the touch display,

which is an additional layer on a liquid crystal display (LCD).

The importance of these components can also be seen in their impact on the performance of

the iPhone. Although such an analysis can be done for many of the components shown in Table 4

and the tradeoffs that are made among them, flash memory is analyzed since storing music, videos,

games, and particularly apps are important to many users. The first iPhone contained either 4 or

8GB of flash memory so we can hypothesize that 4GB was the minimum amount of flash memory

needed before the iPhone was economically feasible for users. According to various sources

(MacWorld, 2015; Wiki, 2015), 4 GB of memory can store about 760 songs, 4000 pictures (4

megapixel JPEG), four hours of video, or 100 apps/games, or some combination of these songs,

photos, video, and apps/games. Equal usage of them would mean a user could store 190 songs,

1000 pictures, one hour of video, and 25 apps/games in an iPhone with 4GB of flash memory.

An eco-systems of app suppliers is often emphasized in discussions of the iPhone’s success

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(Yoffie and Kim, 2010) so flash memory’s impact on them is analyzed in further detail. 1.4 billion

apps had been downloaded by the 26 million people who had purchased an iPhone by July 2009

(Moonshadow, 2015). This means that the average user had downloaded 58 apps, thus

representing a significant fraction (58%) of the 4GB iPhone’s memory capacity. Clearly flash

memory capacity had a large impact on when Apple’s app strategy became economically feasible

and could be introduced.

A sensitivity analysis for the impact of flash memory on iPhone costs also illuminates the

importance of flash memory. The cost of the iPhone 5 varied from $207 to $238 depending on

whether the flash memory capacity was 16GB, 32GB, or 64GB. For the earlier phones, the

differences were even larger. For the iPhone 4s, the costs were between $196 and $254 for the

same range in flash memory. For the iPhone 3GS, 16GB of flash memory are $24 thus suggesting

that the costs for the same change in flash memory capacity were between $179 and $251. In

percentage terms, the same changes in flash memory capacity led to an increase of 40% in the

iPhone 3GS and an increase of only 15% in the iPhone 5. Clearly, improvements in flash memory

have had a large impact on iPhone costs and have enabled users to obtain phones with larger

amounts of memory. Similar analyses can be done for many of the other components shown in

Table 4.

Improvements in flash memory, application processors, and in other components also

impacted on the quality and variety of apps, a type of electronic service, some of which have

destroyed an existing economic system and created a new one. As improvements occurred in flash

memory and microprocessors thus enabling increases in the flash memory capacity and processing

speeds of phones, app developers were able to create more sophisticated apps for new and

interesting applications. Ride sharing (e.g., Uber), hotel (e.g., Airbnb), mobile shopping (e.g.,

Flipkart), and picture sharing (e.g., Snapchat) apps began to proliferate as the improvements in

iPhones occurred. All of the startups in parentheses are now valued at more than $15 billion and

more than other 30 startups that offer these apps were valued at more than $1 billion each as of

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October, 2015 (WSJ, 2015). Although the costs of these apps may not be primarily driven by

standard components as with electronic products, the performance of them were driven by

improvements in phones and the mobile telecommunication systems, and improvements in both

of them were driven by improvements in microprocessors, flash memory, and other electronic

components (Gonzalez, 2010).

One component in the iPhone that is not a standard component is the operating system. Apple

uses its own operating system - iOS - in smart phones, tablet computers, and other products while

Android, which is free from Google, is used by suppliers of other smart phones, tablet computers,

and products. The first versions of these operating systems included the functionality necessary

for the first smart phones to have touch based browsing, which changed the concept of a phone

from voice and texting to touch-based browsing and required a new architecture, one that can be

called a loosely coupled architecture (Yoo et al, 2010). Touch-based browsing required different

linkages between the operating system, touch display, apps, and other components than had

existed in previous phones (McNish and Silcoff, 2015) and thus involved a completely new

architecture. The iOS and the new architecture phone architectural were essential to the success

of the iPhone because they effectively organized the service stack and the user experience around

applications, content and networking (Eaton et al, 2011). Subsequent iPhones can also be

considered architectural innovations, albeit smaller ones than the first iPhone, because there has

been continued changes in the linkages between components: functions have been combined into

fewer chips, electronic and mechanical parts have been moved around to meet form factor goals,

and software, including the operating system and its interface with apps, has been reorganized to

enhance usability.

However, the basic argument of this paper still holds for Apple’s operating system.

Improvements in standard components such as microprocessors and memory enabled this new

form of operating system to become economically feasible. As with all computers, larger and more

sophisticated operating systems require microprocessors that are faster (Maccaba, 2014) and for

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mobile devices, the microprocessors must also have low power consumption (McNish and Silcoff,

2015). These improvements in performance (and price) came about gradually over time and even

the second and third generation iPhones have much faster browsing and lower power consumption

than did the first one. Interestingly, one reason Blackberry was slow to introduce smart phones

was because Blackberry executives did not think consumers would use phones with browsers as

slow and power consuming as the ones in the first iPhones (McNish and Silcoff, 2015); a problem

that was gradually solved as improvements in microprocessors occurred and portable battery

packs became widely available.

4.2 Tablet Computers

Table 5 summarizes the evolution of the iPad. As with the first iPhone, the first iPad is a radical

innovation since it involved changes in both the concept and architecture, as noted above. The

concept of tablet computers involves touch screen browsing while previous computers involve

mouse-based browsing. The first iPad also involved a new architecture, one that can be defined as

a loosely coupled architecture (Yoo et al, 2010). Subsequent versions can also be considered

architectural innovations (Henderson and Clark, 1990) since like smart phones, functions were

combined into fewer chips, electronic and mechanical parts were moved around to meet form

factor goals, and software was reorganized to enhance usability and performance.

As with the iPhone in Table 4, Table 5 organizes the evolution of the iPad by component type

because this is the way Apple and others characterize the improvements. Also similar to the iPhone,

new versions of the iPad have faster and better components. In fact, the components shown in

Tables 4 and 5 are almost the same; the main differences are in the cellular processors and in the

new components that provide new features. Although improved versions of cellular processors are

available in both the iPhones and iPads, cellular processors are a standard feature in the iPhone

and an option in the iPad. For the new features, the iPad includes an accelerometer, light sensor,

magnetometer, gyroscope and barometer, all made possible through new components.

19

The importance of these components can also be seen in their impact on product capability

and cost. Although such an analysis can be done for many of the components shown in Table 5,

displays, flash memory, and cellular processors are analyzed because these components probably

had the largest impact on when the iPad initially became economically feasible. The display

includes the LCD and touch screen. Although time series data on touch screens are not available,

data for LCDs suggests that their costs fell 12% per year on a per area basis between 2001 and

2011 (prices fell by 30%) and thus the cost of displays for the iPad were probably also dropping,

eventually reaching a point at which the iPad was considered economically feasible to users.

The impact of improvements in flash memory and cellular processors for the iPad are also

easy to understand. The cost of the iPad Air, released in late 2013, varies from $274 to $331

depending on whether the flash memory capacity is 16GB, 32GB, or 64GB and whether a cellular

processor for access to the cellular network is available or not. For the earlier iPads, the differences

are even larger. For the iPad3, the costs range from $316 to $409 for the same range in flash

memory and the addition of a cellular processor. For the first iPad, the costs range from $229 to

$346 for the same changes in flash memory and cellular processor. Thus, the first iPad has a cost

increase of more than 50%, the iPad3 has a cost increase of 30%, and the iPad Air has a cost

increase of 21% for the same increases in flash memory capacity and the addition of a cellular

processor. Therefore, two standard components in the iPad, the flash memory and cellular

processor increased the cost of the first iPad by 50% and this extra cost fell to 21% in the iPad Air

as the cost of these standard components fell.

As with the iPhone, one components in the iPad that is not a standard component is the iPad’s

operating system. The operating system for the iPad was borrowed from the iPhone and it included

the functionality necessary for the first iPad to have touch based browsing; this functionality

changed the concept of a computer from mouse-based to touch-based browsing. It also changed

the architecture of a computer and these architectural changes have continued with subsequent

iPads. However, as with the iPhone, the basic argument of this paper still holds for the iPad.

20

Improvements in standard components such as microprocessors and memory enabled this new

form of operating system to become economically feasible since a sufficiently large and

sophisticated operating system required microprocessors that had sufficiently fast speeds and low

power consumption.

5. Interpretation of Results

The previous section showed that the costs of standard components are much higher than that

of assembly costs for a large variety of electronic products. These standard components are mostly

provided by independent component suppliers and are used in many different types of electronic

products. Although some high cost components were designed and/or manufactured by a supplier

of an electronic product such as Samsung or Apple, in these cases the same components were used

in other end products from the same supplier and/or the same types of products from a different

supplier.

The previous section also showed that the evolution of the iPhone’s and iPad’s performance

are characterized by improvements in standard components. This suggests that not only do

standard components represent a large percentage of total costs, they also greatly contribute to

product performance. Engineers used improvements in components to improve component-based

performance measures for the iPhone and iPad and make changes to their overall design. For the

products investigated in this paper, they used improvements in memory to increase the number of

videos, pictures, songs, games, and apps that can be stored in the products. They used

improvements in microprocessors to create and improve a sophisticated operating system and to

make the device compatible with more sophisticated games, apps, and with new cellular, WiFi,

Bluetooth and other communication standards. They used improvements in displays to provide

better resolution and clarity and they used new forms of components such as GPS, accelerometers,

and compasses to provide new features. This is quite different from the system-based design

changes that were described in the literature review for automobiles (Abernathy and Clark, 1985).

21

What does this tell us about how radical innovations such as the first iPhones and iPads

became economically feasible? While most of us will read Tables 4 and 5 from left to right, reading

from right to left can help us understand how the first smart phones and tablet computers became

economically feasible. A product’s performance must exceed a minimum threshold of

performance and its price must fall below a maximum threshold of price before the product will

diffuse (Green and Wind, 1973; Lancaster, 1979; Adner, 2002, 2004; Adner and Zemsky, 2005).

These thresholds can be inferred from Tables 4 and 5 by reading from right to left and by

considering the probably lower performance and higher cost of these products before they were

released. Furthermore, since components have the largest impact on performance and cost for

smart phones and tablet computers, these thresholds can also be defined for specific components

within smart phones and tablet computers.

Consider smart phones for which many argue that touch screens, apps, and a 3G cellular

connection were necessary before they became popular with users. Specific components are

important for each of these functions. A sufficiently sensitive and inexpensive display was needed

so that browsing could be done through touch. Second, inexpensive memory was needed before

an adequate number of songs, pictures, videos, apps, and games could be saved on a smart phone

and Apple’s eco-system of app suppliers became a feasible strategy; Section 4.1 highlighted the

importance of growing memory capacity and falling costs per memory bit. Third, inexpensive and

fast processors were needed before 3G cellular capability could be placed in the phone; the 3G

connection was needed to have adequate data speeds. For each of these components, one can

calculate minimum and maximum thresholds of performance and price respectively for them that

were needed before the iPhone became economically feasible. Except for the touch screen, rates

of improvement trajectories for these components can also help estimate these thresholds.

Furthermore, since the touch screen grew out of improvements in liquid crystal displays and thin-

film processing, its development could also be analyzed if more data is collected.

A similar type of logic can be applied to tablet computers. The larger size of the display for

22

them suggests that the cost of the liquid crystal and touch screen display was probably more

important for tablet computers than for smart phones and this should be reflected in maximum

and minimum thresholds of price and performance for displays in tablet computers Second,

inexpensive WiFi chips (and perhaps a certain density of WiFi locations) were needed before tablet

computers were purchased. Maximum and minimum thresholds of price and performance

respectively can be defined for the WiFi chips, which are basically a type of microprocessor. For

each of these components, one can calculate minimum and maximum thresholds of performance

and price respectively for them that were needed before the iPhone became economically feasible

and except for the touch screen, rates of improvement trajectories for these components could help

estimate these thresholds.

For both tablet computers and smart phones, the existence of standards also helped them

become economically feasible1. Although the literature on them usually emphasizes compatibility

and network size (Shapiro and Varian, 1999), their existence also reduced the minimum level of

performance and raised the maximum level of price that were needed in components for the iPhone

and iPad because standards reduced the technical difficulties of the problems that needed to be

solved. For example, the existence of 3G network standards and WiFi standards reduced the

number of network interfaces for which the relevant ICs and software needed to handle. The

existence of standards for maps, video, music, and external memory also reduced the technical

challenges for designers. Without these standards, more complex software and higher performance

components would have been needed before the iPhone and iPad became economically feasible.

6. Discussion

What is the long-term evolutionary process (Nelson and Winter, 1982; Ziman, 2000; Murmann,

2004) by which new technologies, including ones that can be defined as radical innovations,

1 I am indebted to an anonymous reviewer for this insight.

23

become economically feasible and thus candidates for commercialization? This paper found a

process for electronic products and services that is very different from the traditional emphasis on

distinct stages of invention, commercialization, and diffusion. In spite of their large impact on the

world, i.e., creative destruction, the iPhone (and app-based services), iPad, and other new

electronic products were not invented in a scientific sense so the first stage of this process does

not exist. Although some might argue that the commercialization of the iPhone or iPad represents

a form of invention, arguing for simultaneous invention and commercialization does not illuminate

the long-term evolutionary process by which they became economically feasible.

Second, the costs of the iPhone and iPad were not driven by assembly or other “system” costs.

Instead, the costs of the iPhone, iPad, and other electronic products are primarily driven by the

cost of standard components, which are used in a wide variety of electronic products and by

multiple firms. This suggests that learning and experience curves do not explain the cost

reductions for electronic products such as the iPhone and iPad; the observation about learning

curves is consistent with (Thompson, 2012).

The apparent importance of standard components enables one to work backwards to

understand the performance and price that were needed in these components before the radical

innovations of the first iPhones and iPads, including their app-based eco-systems (Yoffie and Kim,

2010), would begin to sell. This analysis and in particular the analysis of flash memory and apps

suggests that the economics of the first iPhones and iPads were highly dependent on the price and

performance of flash memory, microprocessors, displays, and other electronic components. As the

components were improved, the concept of an iPhone and iPad became economically feasible,

they were introduced by Apple, and both diffusion and further improvements occurred. Along with

the introduction and diffusion of the iPhone and iPad, a similar set of dynamics enabled better

apps to emerge and diffuse.

This has important implications for firms must “look forward and reason back,” in order to

develop good strategies (Yoffie and Cusumano, 2015). Managers and policy makers must think

24

about the types of products and services that are likely to emerge as improvements in standard

components continue. Then they must think about which ones are the best opportunities for them

and what types of strategies are made possible by the improvements in standard components (e.g.,

app-based strategy). Only after doing these two things does the traditional literature on technology

implementation become useful (Geels, 2002, 2004; Ansari and Garud, 2008).

6.1 Theoretical Contributions

How does this paper’s results advance our understanding for evolutionary theories of

technology change? Three key issues in theories of evolutionary change are combinatorial

learning, recursion (Fleming, 2001; Fleming and Sorenson, 2001; Arthur, 2007, 2009), and variety

creation (Nelson and Winter, 1982; Ziman, 2000; Murmann, 2004), all of which can be subsumed

under the general term, “technology paradigm” (Dosi, 1982; Dosi and Nelson, 2010). For the first

three, while recombinant search among components may be a critical aspect of recursion and

variety creation for many products (Basalla, 1988; Fleming, 2001; Fleming and Sorenson, 2001;

Arthur, 2007), it is probably of less importance when standard components contribute most of the

performance and cost and these components are experiencing rapid improvements.

When standard components are important, the combinatorial learning, recursion and variety

creation revolve around them as engineers conceive of new products that might be made possible

by rapid improvements in standard components. Even when the new products are radical or

architectural innovations, engineers consider the levels of performance and cost in the components

that are needed before the performance and price of possible end products will exceed minimum

thresholds of performance and fall below maximum thresholds of price. As rapid improvements

in electronic components continue, the variety of products and services to consider continues to

grow.

This paper also has implications for recursion and variety creation once an engineer or a firm

has decided to focus on a specific type of product. Once a type of product has been chosen,

25

engineers must think about the value proposition and the customers (Chandy and Tellis, 1998).

They must think about the value proposition that a product can provide with existing components,

whether this value proposition is sufficient for customers, for which customers might this value

proposition be sufficient, and the impact of improved components on the value proposition and

architectural design for the product (Ulrich, 1995; Yoo et al, 2010). These questions are considered

recursively as a product proceeds from conceptual to detailed design and they will continue to be

relevant even after a product is commercialized.

This discussion suggests that electronic products and services have a different type of

technology paradigm (Dosi, 1982; Dosi and Nelson, 2010) from science-based products. While

science strongly impacts on how problems are solved and improvements are achieved for some

products and services, improvements in electronic components have a strong impact on many

aspects of electronic products and services. This include their direction and rates of change, the

types of problems that are solved, the way in which improvements are achieved, and thus the

direction of the entire electronics sector.

Second, electronic products involve multiple standard interfaces often at different layers in an

overall architecture (Baldwin and Clark, 2001) and many of these standards come from a wide

eco-system of firms. Each layer in the architecture (Yoo et al, 2010) involves both competition

between firms and between standards, where each competing standard is often supported by an

eco-system of firms (Adomavicius, 2008). This existence of standards and thus the competition

among them impacts on the levels of performance and price that are needed in standard

components before a new product or service becomes economically feasible. Furthermore, the

competition in the eco-system and the entry of new firms impacts on how these standard

components are assembled into higher-level standard modules and on the development of

complementary technologies such as algorithms and design tools.

6.2 Generalizability

26

How broadly is this paper’s analysis applicable? It is likely that this analysis is applicable to

radical innovations for a wide variety of electronic products including the nine products analyzed

in this paper. It can also probably help engineers analyze new forms of drones, scanners, 3D

printers, smart watches, driverless vehicles, and wearable computing, and applications for the

Internet of things. While mechanical products mostly have mechanical components, adding an

internet connection primarily involves electronic components. This will become economically

feasible when the cost of the components is lower than the value added (performance) of the

components where the value added will probably depend on the product types.

This paper’s analysis can also help find low-end disruptive innovations (Christensen, 1997).

Christensen’s theory implies that all the improvements in new forms of electronic products are

driven by the demand for these new products and that the introduction of the first successful

product is a key event that stimulates R&D in the new product. He has made this argument for

many types of computers, of electronic products including the Walkman (Christensen et al, 2001),

and of hard disk drives (Christensen, 1997). However, the high contribution of microprocessors,

semiconductor memory, hard disk memory, and monitors to the cost of computers and other

electronic products suggests that the improvements in new forms of electronic products have been

primarily driven by improvements in components and thus the impact of demand on the

improvements in the new product have been much less important than is emphasized by

Christensen. Thus, in order to find potential disruptive innovations, this paper’s results suggest

one should look for component technologies that are experiencing rapid improvements and that

enable the emergence of low-end products.

This paper’s results are also applicable to Internet content, services and software (Lyytinen

and Rose, 2003) including the Internet’s telecommunication system, servers, routers and

computers (Funk, 2013a). For example, for e-commerce sites, the cost for users primarily depends

on the cost of the Internet services and the performance of the content (e.g., pictures, videos)

depends on the bandwidth, cost, and latency of the Internet. Improvements in the Internet have

27

enabled music and video services, the greater usage of pictures, videos, and flash content on

websites, and new forms of advertising to emerge (Downes and Nunes, 2014; WebSite, 2015).

Similar arguments can be made for new forms of cloud computing, big data, and software and the

importance of architectures and standards for them. Thus, engineers can use this paper’s

description to look for new types of Internet content, services, and software and future research

should explore this issue further.

7. Conclusions

This paper describes an evolutionary process by which new forms of electronic products and

services become economically feasible that is very different than the predominant viewpoint of

invention, commercialization, and diffusion. The new forms of electronic products and services

are not invented in a scientific sense and the cost and performance of them are primarily driven

by improvements in standard components. Thus, these new products and services initially become

economically feasible as the cost and performance of standard electronic components reach the

levels necessary for the new products and services to become economically feasible. This suggests

that the composition of new technologies, the impact of components on a technology’s cost,

performance and design, and the rates of improvement in the components are important things to

consider when managers, policy makers, and engineers consider the choice and timing of

commercializing new electronic products and services.

28

Quantity

Price

q

Figure 1. Supply and Demand Curves and Maximum Threshold of Price

Demand Curve

Supply Curve

Typical movement ofsupply curve over time

Maximumthresholdof price

29

Table 1. Example of Cost Data Published for Apple iPhone 5s

Cost Element Details Cost of Phone for different

amounts of flash memory

16GB 32GB 64GB

NAND Flash $9.40 $18.80 $29.00

DRAM 1GB LPDDR3 $11.00

Display and Touch

Screen 4” Retina Display w/Touch $41.00

Processor 64-Bit A7 Processor + M7 Co-Processor $19.00

Camera 3MP (1.5 micron)+1.2MP $13.00

Wireless Section-

BB/RF/PA

Quallcom

MDM9615+WTR1605L+Front End $32.00

User Interface and

Sensors Includes fingerprint sensor assembly $15.00

WLAN/BT/FM/GPS Murata Dual-Band Wireless-N Module $4.20

Power Management Dialog+Qualcomm $7.50

Battery 3.8V~1560mAh $3.60

Mechanical/Electro-

mechanical $28.00

Box Contents $7.00

Total Materials $190.70 $200.10 $210.30

Final Assembly $8.00

Total Costs $198.70 $208.10 $218.30

Source: (IHS, 2013)

30

Table 2. Cost Breakdown for Electronic Products for Assembly and Standard Components

Type of

Product

Final Assembly Standard Components1

Number

of Data

Points

Average

cost (%)

Standard

Deviation3

Number

of Data

Points

Average cost2

(%)

Standard

Deviation3

Smart

Phones

28 4.2% 0.011 26, 28 76%, 79% 0.10,

0.10

Tablet

Computers

33 3.1% 0.010 33, 33 81%, 84% 0.033,

0.032

eBook

Readers

6 4.0% 0.0064 6, 9 88%, 88% 0.037,

0.031

Laptop

Computers

3 2.7% 0.0070 Not available

Game

Consoles

2 2.6% 0.0039 2, 2 78%, 80% 0.19,

0.19

MP3

Players

2 3.4% 0.0052 2, 9 74%, 76% 0.0087,

0.081

Large

Screen

Televisions

2 2.4% 0.0057

2, 2 82%, 84% 0.041,

0.038

Internet

TVs

2 5.7% 0.0052 2, 2 57%, 61% 0.067,

0.075

Google

Glass

1 2.7% Not

Applicable

1, 1 62%, 64% Not

Applicable

1 Standard components exclude mechanical components, printed circuit boards, and passive

components

2 Average costs as a percent of total and material costs, figures are separated by commas

3 Standard deviations are in decimal form while averages are in percentages

31

Table 3. Percentage of Standard Components for Products Shown in Table 1

Type of

Product

Number

of Data

Points

Memory Micro-

Processor

Display Camera Connectivity

& Sensors

Battery Power

Management

Smart

Phones

23 15% 22% 22% 8.2% 7.9% 2.3% 3.8%

Tablet

Computers

33 17% 6.6% 38% 2.9% 6.3% 7.3% 2.5%

eBook

Readers

9 10% 8.1% 42% .30% 8.3% 8.3% Not available

Game

Consoles

2 38% 39% none none Not available none 5.8%

MP3

Players

9 53% 9% 6% none Not available 4% 3.5%

Televisions 2 7% 4.0% 76% none Not available none 3.0%

Internet

TVs

2 16% 31% none none 10.5% none 3.5%

Google

Glass

1 17% 18% 3.8% 7.2% 14% 1.5% 4.5%

32

Table 4. Evolution of iPhone in Terms of Measures of Performance

Measure iPhone iPhone 3G iPhone 4 iPhone 5 iPhone 6

Operating System 1.0 2.0 4.0 6.0 8.0

Flash Memory 4, 8, or 16GB 8 or 16GB 8, 16, or 64GB 16, 32 or 64GB 16, 64, or 128GB

DRAM 128MB 128MB 512MB 1GB 1GB

Application

Processor

620MHz Samsung 32-bit RISC

ARM

1 GHz dual-core

ARM Cortex-A9

Apple A5

1.3 GHz dual-core

ARMv7s Apple A6

1.4 GHz dual-core ARM v8-A

65-bit Apple A8, M8 motion

co-processor

Graphics Processor PowerVR MBX Lite 38 (103

MHz)

PowerVR

SGX535 (200

MHz)

PowerVR

SGX543MP3 (tri-

core, 266 MHz)

PowerVR GX6450 (quad-

core)

Cellular Processor GSM/GPRS/

EDGE

Previous plus

UMTS/ HSDPA

3.6Mbps

Previous plus

HSUPA 5.76Mbps

Previous plus LTE,

HSPA+, DC-

HSDPA, 14.4Mbps

Previous plus LTE-Advanced,

14.4Mbps

Display resolution 163 ppi 326 ppi 401 ppi

Camera resolution

Video speed

2 MP 5 MP

30 fps at 480p

8 MP

30 fps at 1080p

8 MP

60 fps at 1080p

WiFi 802.11 b/g 802.11 b/g/n 802.11 a/b/g/n 802.11 a/b/g/n/ac

Other Bluetooth 2.0 GPS, compass,

Bluetooth 2.1,

gyroscope

GPS, compass, Blue-

tooth 4.0, gyroscope,

voice recognition

Previous plus finger-print

scanner, near-field

communication

ppi: pixels per inch; mbps: mega bits per second; 480p: progressive scan of 480 vertical lines; MP: mega pixels

33

Table 5. Evolution of iPad in Terms of Measures of Performance

Measure iPad iPad2 iPad3 iPad4 iPad Air iPad Air 2

Operating System 5.1.1 iOS 8

System on Chip Apple A4 Apple A5 Apple A5X Apple A6X Apple A7 Apple A8X

Application Processor 1 GHz ARM Cortex-

A8

1 GHz dual-core ARM

Cortex-A9

1.4 GHz dual-

core Apple Swift

1.4 GHz dual-core

Apple Cyclone

1.5 GHz tri-core

Graphics Processor PowerVR SGX535 Dual-core

PowerVR

SGX543MP2

Quad-core

PowerVR

SGX543MP4

Quad-core

PowerVR

SGX554MP4

Quad-core

PowerVR G6430

Octa-core

PowerVR

GXA6850

Flash Memory 16, 32, or 64 GB 16, 32, 64, or 128 GB 16, 64, 128 GB

DRAM 256 MB 512 MB 1 GB 2GB

Display 132 ppi 264 ppi

Camera resolution, video

speed, digital zoom

None .7 MP, 30fps

5 times

5 MP, 30fps,

5 times

8 MP, 30 fps

3 times

Wireless without cellular Wi-Fi 802.11a/b/g/n; Bluetooth 2.1 Wi-Fi 802.11a/b/g/n; Bluetooth 4.0

802.11a/b/g/n/ac

Bluetooth 4.0

Wireless w/cellular Above plus 2G EDGE, 3G HSDPA Above and left plus LTE

Geolocation without

cellular

WiFi, Apple location database Previous plus

iBeacon

Geolocation with cellular Assisted GPS, Apple databases,

cellular network

Previous plus GLONASS (Russian-based GPS) Previous plus

iBeacon

Other Accelerometer, light

sensor, magnetometer

Previous plus gyroscope Previous plus

barometer

ppi: pixels per inch; MP: mega pixels; fps: frames per second;

34

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