After showing that the costs of most electronic products are from electronic components, these slides show how the iPhone and iPad became economically feasible through improvements in microprocessors, flash memory, and displays.

1. Technology change, economic feasibility, and
creative destruction: the case of new electronic
products and services
Jeffrey Funk*
Independent Technology Consultant, Department of Engineering and Technology Management, National
University of Singapore, 7 Engineering, Block E3A, Fourth Floor, 117574, Singapore. e-mail:
jeffreyleefunk@gmail.com
*Main author for correspondence.
Abstract
This article 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 predomin-
ant 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 ser-
vices 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, pol-
icy 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.
JEL classification: O31, O32, O33.
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 (ICs), 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, ser-
vices, 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
VC The Author 2017. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved.
Industrial and Corporate Change, 2017, 1–18
doi: 10.1093/icc/dtx021
Original article

2. forward and reason back,” 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 evolu-
tionary process (Nelson and Winter, 1982; Ziman, 2000; Murmann, 2004) by which new technologies become eco-
nomically 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 dif-
ferent 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, 1983) 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, 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 improve-
ments in performance and cost along an experience curve (Dutton and Thomas, 1984; Lieberman, 1984;
Balasubramanian and Lieberman, 2010).
This article considers important types of products and services for which an alternative process is more appropri-
ate 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 prod-
ucts and services is 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 past 50 years (Funk and Magee, 2015).
This article proceeds as follows. It first surveys the literature on how new technologies become economically feas-
ible 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 longitu-
dinal data on the iPhone, iPad, and their components, it works backward to understand the process by which they
and their associated services became economically feasible. Sixth, it uses this analysis to propose an evolutionary pro-
cess 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 tech-
nology 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 per-
formance 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 lev-
els of performance and maximum levels of price for each user represented by the demand curve in Figure 1 where
2 J. Funk

3. 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 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) 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, 1983) in which ad-
vances 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 phe-
nomena (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 quantum computers. Also before commer-
cialization, 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 re-
ductions in scale (Funk and Magee, 2015).
The creation and demonstration (i.e., invention) of new concepts is also sometimes facilitated by advances in sci-
ence. 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,
QuanƟty
Price
q
Demand
Curve
Supply Curve
Typical movement of
supply curve over Ɵme
Maximum
threshold
of price
Figure 1. Supply and demand curves and maximum threshold of price.
Technology change, economic feasibility, and creative destruction 3

4. 1991), television (Bilby, 1986), semiconductors (Tilton, 1971), lasers, light-emitting diodes (Orton, 2009), and liquid
crystal displays (LCDs, Castellano, 2005).
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; Balasubramanian 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 mech-
anical 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 prod-
ucts 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 im-
provements 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 feas-
ible and thus candidates for commercialization and creative destruction. Many of the recently defined GPTs are
electronic components or electronic products/systems. Examples of the former include ICs, and lasers and ex-
amples 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,
2004, 2005), and economic growth (Oliner and Sichel, 2002; Oliner et al., 2007; Jorgenson et al., 2008), where it
is recognized that improvements in standard ICs are the sources of the improvement in computers by computer sci-
entists (Smith, 1988), 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 prod-
ucts 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 18–24 months for many years, resulting in relatively constant annual
rates of improvement of 30–40% 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 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 article is to ana-
lyze 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
4 J. Funk

5. might impact on these required levels? How can decision makers use knowledge of these factors and the overall pro-
cess 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 2007–2014. 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 were found, iSuppli and TechInsights
publish cost data, some for clients and some for the public, and the public data include 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,
which can be higher and impact on competition). 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 includes 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.
Second, once the data were 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 inter-
faces, this article 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 mul-
tiple 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 article.
To better explain the definition of standard components used in this article, Table 1 shows the typical data that
are available for electronic products, in this case Apple’s iPhone 5s. It shows the costs for 11 categories of materials
and for assembly and total cost. It also shows the specifications for nine different components, all of which are de-
signed (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, and 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 compo-
nents in the first-generation iPhone and the iPhone 3 but are defined as standard components in the iPhone 5s (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) has made touch screen technology a standard component
that is available in a wide variety of electronic products.
Thus, except for the mechanical, electromechanical, 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 electromechanical 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 are available for passive electronic components such as filters that are used by many phone sup-
pliers. 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 article’s analysis to underestimate the contri-
bution of standard components to costs.
The third step in this article’s analysis was to place the standard components into multiple categories. The infor-
mation 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 were 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
Technology change, economic feasibility, and creative destruction 5

6. products both as an engineer early in his career and as a researcher and consultant on these products over the past
20 years.
Fourth, detailed information was 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 improve-
ments and how are they different from the design changes that enabled improvements in other products such as auto-
mobiles (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.
Fifth, the information on the evolution of the iPhone and iPad was used to better understand how they first
emerged by working backward 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 ecosystem of apps is 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. These data demonstrate that final assembly represents a small percentage of costs and that standard
components represent a much larger percentage of costs than does final assembly. Final assembly represents less than
Table 1. Example of cost data published for Apple iPhone 5s
Cost element Details Cost of phone for different amounts of flash memory
16 GB 32 GB 64 GB
NAND flash $9.40 $18.80 $29.00
DRAM 1 GB LPDDR3 $11.00
Display and touch screen 4" retina display w/touch $41.00
Processor 64-bit A7 processorþM7 co-processor $19.00
Camera 3MP (1.5 micron)þ1.2MP $13.00
Wireless section-BB/RF/PA Quallcom MDM9615 þ WTR1605L þ Front End $32.00
User interface and sensors Includes fingerprint sensor assembly $15.00
WLAN/Bluetooth/FM/GPS Murata dual-band wireless-N module $4.20
Power management DialogþQualcomm $7.50
Battery 3.8V1560 mAh $3.60
Mechanical/electromechanical $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).
6 J. Funk

7. 6% of total costs for all of the nine product types, and it is less than 3% for laptop computers, game consoles, televi-
sions, and Google Glasses. Standard components represent more than 55% of total cost and more than 60% of ma-
terial 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 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 cover 2007–2014 suggest that assembly costs have always
represented a small percentage of total costs, and that standard components have always represented a large percent-
age 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 break-
downs, 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 prod-
uct, but that the data are not available.
Table 2. Cost breakdown for electronic products for assembly and standard components
Type of product Final assembly Standard componentsa
Number of
data points
Average
cost (%)
Standard
deviationc
Number of
data points
Average
costb
(%)
Standard
deviationc
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
a
Standard components exclude mechanical components, printed circuit boards, and passive components.
b
Average costs as a percent of total and material costs, and figures are separated by commas.
c
Standard deviations are in decimal form while averages are in percentages.
Table 3. Percentage of standard components for products shown in Table 1
Type of product Number of
data points
Memory
(%)
Microprocessor
(%)
Display
(%)
Camera
(%)
Connectivity and
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 0.30 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
Technology change, economic feasibility, and creative destruction 7

8. Looking at Table 3 in more detail, we begin with memory and move to the right. SRAM (static random-access
memory), DRAM, 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 prod-
ucts 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 proces-
sors, one for internal processing of music, video, and other applications; and one for interacting with the cellular net-
work, have been used for many years, but they have been integrated into a single chip in some cases (ISSCC, 2013).
The bills of materials from iSuppli and TechInsight suggest that more than 90% of smart phones use one of six stand-
ard processors from five suppliers (Travlos, 2012; Peddie, 2014; Kondajjala, 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 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 stand-
ard 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 compo-
nents 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 econom-
ically 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 innov-
ation, 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
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 16 GB 8 or 16 GB 8, 16, or 64 GB 16, 32 or 64 GB 16, 64, or 128 GB
DRAM 128 MB 128 MB 512 MB 1 GB 1 GB
Application
processor
620 MHz
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
3.6 Mbps
Previous plus HSUPA
5.76 Mbps
Previous plus LTE,
HSPAþ, DC-HSDPA,
14.4 Mbps
Previous plus
LTE-Advanced,
14.4 Mbps
Display resolution 163 ppi 326 ppi 401 ppi
Camera resolution 2 MP 5 MP 8 MP 8 MP
Video speed 30 fps at 480p 30 fps at 1080p 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, and
gyroscope
GPS, compass, Blue-tooth
4.0, gyroscope and
voice recognition
Previous plus finger-print
scanner and near-field
communication
Note: ppi: pixels per inch; mbps: mega bits per second; 480p: progressive scan of 480 vertical lines; MP: mega pixels.
8 J. Funk

9. 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 and others charac-
terize the improvements. New versions of the iPhone have more memory, faster and better processors, higher-reso-
lution displays and cameras, faster and higher resolution video cameras, faster WiFi, and Bluetooth, and new
features such as compasses, gyroscopes, voice recognition, fingerprint 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 appli-
cation 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 compatibil-
ity 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,
fingerprint 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 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 trade-offs 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 8 GB of flash memory, so we can hypothesize that 4 GB was the min-
imum 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), 4 h 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, 1 h of video, and 25 apps/games in an iPhone
with 4 GB of flash memory.
An ecosystem of app suppliers is often emphasized in discussions of the iPhone’s success (Yoffie and Kim, 2010),
so flash memory’s impact on them is analyzed in further detail. In total, 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 4 GB 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
16, 32, or 64 GB. 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, 16 GB of flash memory are $24, thus sug-
gesting 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 cre-
ated 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 start-
ups in parentheses are now valued at more than $15 billion, and more than other 30 start-ups that offer these apps
were valued at more than $1 billion each as of 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 was driven by im-
provements 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).
Technology change, economic feasibility, and creative destruction 9

10. One component in the iPhone that is not a standard component is the operating system, whose development costs
can be in the billions of dollars and thus must be amortized over many unit sales of the same or related products.
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 ver-
sions 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, be-
cause 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 article 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 economic-
ally feasible. As with all computers, larger and more sophisticated operating systems require microprocessors that are
faster (Macccaba, 2014), and for 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 execu-
tives 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 soft-
ware was reorganized to enhance usability and performance.
As with the iPhone in Tables 4 and 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, magnetom-
eter, gyroscope, and barometer, all made possible through new components.
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 pro-
cessors 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 suggest 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 was 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 is 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 16, 32, or 64 GB, and whether a cellular processor for access to the cellular network is available. For the earlier
10 J. Funk

11. Table5.EvolutionofiPadintermsofmeasuresofperformance
MeasureiPadiPad2iPad3iPad4iPadAiriPadAir2
Operatingsystem5.1.1iOS8
SystemonchipAppleA4AppleA5AppleA5XAppleA6XAppleA7AppleA8X
Applicationprocessor1GHzARM
Cortex-A8
1GHzdual-core
ARMCortex-A9
1.4GHzdual-core
AppleSwift
1.4GHzdual-core
AppleCyclone
1.5GHztri-core
GraphicsprocessorPowerVRSGX535Dual-corePowerVR
SGX543MP2
Quad-corePowerVR
SGX543MP4
Quad-corePowerVR
SGX554MP4
Quad-corePowerVR
G6430
Octa-corePowerVR
GXA6850
Flashmemory16,32,or64GB16,32,64,or128GB16,64,128GB
DRAM256MB512MB1GB2GB
Display132ppi264ppi
Cameraresolution,
videospeed,digitalzoom
None0.7MP,30fps5MP,30fps8MP,30fps
5times5times3times
WirelesswithoutcellularWi-Fi802.11a/b/g/n;Bluetooth2.1Wi-Fi802.11a/b/g/n;
Bluetooth4.0
802.11a/b/g/n/ac
Bluetooth4.0
Wirelessw/cellularAboveplus2GEDGE,3GHSDPAAboveandleftplusLTE
GeolocationwithoutcellularWiFi,ApplelocationdatabasePreviousplusiBeacon
GeolocationwithcellularAssistedGPS,Appledatabases,andcellular
network
PreviousplusGLONASS
(Russian-basedGPS)
PreviousplusiBeacon
OtherAccelerometer,lightsensor,andmagnetometerPreviousplusgyroscopePreviousplusbarometer
Note:ppi:pixelsperinch;MP:megapixels;fps:framespersecond.
Technology change, economic feasibility, and creative destruction 11

12. 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 cap-
acity 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 component 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 article still holds for the iPad.
Improvements in standard components such as microprocessors and memory enabled this new form of operating sys-
tem to become economically feasible, since a sufficiently large and sophisticated operating system required micropro-
cessors that had sufficiently fast speeds and low power consumption.
Nevertheless, Apple’s iOS has had a strong impact on Apple’s success in the iPad, iPhone and other products, and
it will probably have a similar impact on Apple’s success in future products and the economic feasibility of them. The
architecture of software (and its overall performance) is a key factor in the success of most electronic products, and
as the Internet of things spreads to mechanical products, software will become a key factor in competition among
them and their economic feasibility. Mechanical engineering firms such as GE are becoming software firms, and soft-
ware will impact on competition along with the economic feasibility for new forms of mechanical products such as
the Internet of things and driverless vehicles.
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 sup-
pliers and are used in many different types of electronic products. Although some high-cost components were de-
signed 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 differ-
ent supplier.
The previous section also showed that the evolution of the iPhone’s and iPad’s performance is characterized by
improvements in standard components. This suggests that not only do standard components represent a large per-
centage of total costs, they also greatly contribute to product performance. Engineers used improvements in compo-
nents to improve component-based performance measures for the iPhone and iPad and make changes to their overall
design. For the products investigated in this article, 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 microproces-
sors to create and improve a sophisticated operating system and to make the device compatible with more sophisti-
cated games, and 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).
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 under-
stand 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.
12 J. Funk

13. Consider smart phones for which many argue that touch screens, apps, and a 3G cellular connection were neces-
sary before they became popular with users. Specific components are important for each of these functions. A suffi-
ciently 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 ecosystem 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 ad-
equate data speeds. For each of these components, one can calculate minimum and maximum thresholds of perform-
ance 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 LCDs and thin-film processing, its development
could also be analyzed if more data are collected.
A similar type of logic can be applied to tablet computers. The larger size of the display for 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 be-
fore 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
feasible.1
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 prob-
lems 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, become economically feasible and thus
candidates for commercialization? This article found a process for electronic products and services that is very differ-
ent 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 elec-
tronic 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 simultan-
eous 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 backward to understand the performance
and price that were needed in these components before the radical innovations of the first iPhones and iPads,
1 I am indebted to an anonymous reviewer for this insight.
Technology change, economic feasibility, and creative destruction 13

14. 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,” to develop good strategies
(Yoffie and Cusumano, 2015). Managers and policy makers must think 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 com-
ponents (e.g., app-based strategy). Only after doing these two things does the traditional literature on technology im-
plementation become useful (Geels, 2002, 2004; Ansari and Garud, 2008).
6.1 Theoretical contributions
How does this article’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 var-
iety 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 com-
ponents 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 improve-
ments in electronic components continue, the variety of products and services to consider continues to grow.
This article 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, engineers must think about the value propos-
ition 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 en-
tire 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 ecosystem of firms. Each layer in the
architecture (Yoo et al., 2010) involves both competition between firms and between standards, where each compet-
ing standard is often supported by an ecosystem of firms (Adomavicius et al., 2008). This existence of standards and
thus the competition among them impacts on the levels of performance and price that are needed in standard compo-
nents before a new product or service becomes economically feasible. Furthermore, the competition in the ecosystem
and the entry of new firms impact on how these standard components are assembled into higher-level standard mod-
ules and on the development of complementary technologies such as algorithms and design tools.
14 J. Funk

15. 6.2 Generalizability
How broadly is this article’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 article. It can also probably help en-
gineers analyze new forms of drones, scanners, 3D printers, smart watches, driverless vehicles, 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 article’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 prod-
ucts and that the introduction of the first successful product is a key event that stimulates RD 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, semi-
conductor 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 compo-
nents, and thus, the impact of demand on the improvements in the new product has been much less important than is
emphasized by Christensen. Thus, to find potential disruptive innovations, this article’s results suggest one should
look for component technologies that are experiencing rapid improvements and that enable the emergence of low-
end products.
This article’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 and videos) depends on the bandwidth, cost, and latency of the Internet. Improvements in the
Internet have enabled music and video services, the greater usage of pictures, videos, and flash content on Web sites,
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 article’s description to look for new types of Internet content, services, and soft-
ware, and future research should explore this issue further.
7. Conclusions
This article describes an evolutionary process by which new forms of electronic products and services become eco-
nomically feasible that is very different than the predominant viewpoint of invention, commercialization, and diffu-
sion. 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 com-
position 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 engin-
eers consider the choice and timing of commercializing new electronic products and services.
Acknowledgements
The author would like to thank the editor and an anonymous reviewer for comments. Any mistakes are his responsibility.
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