innovation lit review

7/31/2019 Innovation Lit Review

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Innovation and R&Ds effects on firm success, methods

of R&D, first mover effects,

And the anchor-tenant hypothesis

Tyson Smith


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Introduction:

This paper will serve as an annotated bibliography/literature review of the various effects of

innovation and research and development. Topics included will be the curse of the first -

mover, competition and policys effect on innovation, incremental innovation vs. pure

innovation, the effects of an anchor-tenant or a large firm with positive externalities,

collaborative or cooperative R&D vs. in-house R&D and outsourced R&D, how a small firms

approach to R&D effects their success, value of consumer innovation and its potential to

benefit firms, and the effect of venture capital on R&D.

Methodology:

This paper will summarize and conglomerate previous works with mostly survey data from the

US and the UK. Data collection and analysis will be summarized for the individual papers.

Papers include (but are not limited to):

Gourville (2005), Rayna & Striukova (2009), Banbury & Mitchell (1995), Von Hippel (2005), , von

Hippel, de Jong & Flowers (2011), Ahn (2003), Agrawal & Cockburn (2003), Cassiman &

Veugelers (2002), Sampson (2003), Baldwin (1995), Kortum & Lerner (2008).


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Summary of Findings:

The curse of the first-mover is a result of reference dependence, loss aversion, and the

endowment effect. Incremental innovation is strongly positively related to market share; the

greater number of incremental innovations a firm is first to the market with, adopts an

innovation within 4 years of the original release, and the sooner the firm adopts an innovation.

Lead-user driven R&D results in significantly more novel ideas, addressed customer needs more

effectively, and had a higher probability of success than non lead-user driven R&D. 6.1 percent

of consumers in the UK create or modify the products they buy, of which only 2 percent protect

their intellectual property, while 17 percent of the innovators diffused their ideas freely to

others. R&D is positively related to innovation via number of patents to a certain level, then

becomes negatively related after some maximizing point relative to firm size. Multifactor

productivity is also positively related to R&D. Numbers ofeconomic regulations and barriers to

trade are have a negative relationship with R&D, and thus decrease innovation. Anchor tenants

have positive intellectual externalities on their surrounding area, having a direct positive effect

on the numbers of papers published in the geographic area around them. Combining in-house

R&D, working cooperatively with other firms on R&D, and purchasing external R&D increase

number of innovative products released, and cooperation is most effective when the diversity

of technologies between cooperating firms is intermediate. Small firms greatly underestimate

the importance of R&D, and those who invest the most in their innovations have higher

reported sales from new products.


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Literature Review:

Theory and Background: Curse of the First-Mover

Gourville (2005) analyzes why highly innovative products fail at high rates, the so called

curse of the first-mover. His argument is that there is a significant difference in perceived

value of an innovative product between the consumers and the developers of the new product.

He cites that according to Cierpicki, Wright, & Sharp (2000), 40 percent to 90 percent of new

products fail to gain market acceptance. Gourville claims the effects most influential in

innovation failures are reference dependence and loss aversion, with the endowment effect

being the most revealing. He uses an experiment from Kahneman, Knetsch and Thaler (1990) to

illustrate these effects in which students were split into two groups, where one group received

a coffee mug and the other did not. Those who received the mugs were the sellers and were

asked what amount of money they would sell the mug for, and those who did not receive mugs

were the choosers and were asked how much they would spend for the mug. The median

value for the sellers was $7.12 and was only $3.12 for the choosers, as the sellers have loss

aversion for the value of the mug and the choosers have reference dependence relative to how

much added value the mug would provide. Gourville outlines a behavioral model that shows

the more that a customer would have to alter their behavior to use a new, innovative product,

the lower the success rates, and incremental innovation has higher success rates than radical

innovation.


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Rayna & Striukova (2009) also analyze the curse of the first-mover and investigate the

relations between both incremental and radical innovation on market dominance. They use a

case study of four products of varying levels of innovativeness released by Apple, as well as

using anecdotal evidence from several other companies. Rayna & Striukova believe that the

determinants of a first-mover being cursed are technology maturity (the market has sufficient

technology to utilize the innovative product), expertise of customers, network externalities

(value attributed to a product is linearly related with the numbers of consumers using it),

switching costs to adjust for competitor entry (Natural switching costs intrinsic to market:

transportation, time, learning/training. Artificial switching costs created by firms: contracts

with phone providers, know-how, cost of intellectual property rights, and complementary

assets such as business partners, customers, reputation).

They then proceed with the case study of Apples radical and incremental innovations.

Lisa, the first PC with a GUI, failed because it cost far too much money - the equivalent of

$20,893 today. There were no complementary assets, as third-party programmers chose the

IBM PC model instead, and the only devices compatible were proprietarily Apple products. The

Apple Newton was the first PDA, commercially released in 1993. The Newton was also too

expensive, lacked compatibility with existing systems, and had high associated switching costs.

Soon after, Palm released the Palm Pilot and though it was less technologically advanced, it was

smaller and easier to use, and it soon dominated the market. Apples real success started with

its incremental innovation, the iMac, in 1998. It used industry standard peripheral attachments

(USB, Ethernet) and did essentially the same thing a PC did but in a more simplified and

attractive manner, allowing for color customization. Even more successful was the iPod, an


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incremental innovation of an mp3 player released in 2001, four years after the first mass-

produced mp3. It also did not revolutionize the product, just simplified it and made it more

attractive. It was compatible with Macs and minimized switching costs by releasing a software

update to allow it to work with PCs. The reduction of switching costs, increase of technological

maturity, and decrease in required expertise of customers allowed the incremental innovations

of Apple to gain significant market share.

Effects of Incremental Innovation:

Banbury & Mitchell (1995) looks at the effect of incremental innovation on market

share, and how difference in market share changes how firms benefit from incremental

innovation. They go into their data analysis with six hypotheses about incumbent firms:

1) The more times they are the first to introduce incremental innovations, the greater

their market share will be.

2) The more times they adopt incremental innovations, the greater their market share

will be.

3) The sooner they introduce incremental innovations, the greater the market share.

4) The more competitors that offer similar products, the smaller the incumbents market

share.


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5) Incremental innovation only influences business survival by changing the businesss

market share.

6) The more competitors that offer similar products, the more likely that an incumbent

firm will shut down.

To test their hypotheses, Banbury & Mitchell use data from the implantable cardiac

pacemaker industry in America from 1960 to 1990, an industry with a high importance of

product reliability. The data uses archival sources to document incremental innovation for

pacemakers, which started in 1963, identifying 11 successful and revolutionary incremental

innovations in the industry over the period. They used a generalized least squares linear

regression to predict the dependent variable for market share, and the independent variables

that were used were how many times out of 11 that the firm was the first to bring an

innovation to market, how soon it was adopted, how many competitors adopted the innovation

and how long it took them, total number of competitor introductions, market share at the time

of the most recent innovation, and a lagged variable of the market share. The results can be

seen in Table 1.

Banbury & Mitchell find market share was greater the more times an incumbent was

among the first to introduce one of the 11 incremental innovations. If a firm adopted an

innovation within 2-3 years of its initial release, its market share increased. After the 4

th

year

past introduction, adoption of the innovation has a negative relationship with market share.

These results confirmed Hypotheses 1, 2, and 3. Hypothesis 4 does not hold until at least 4

years after adoption, as the data shows that market shares were greater for firms that were the


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first to introduce innovations, even as the number of firms offering similar products increased

for the first 4 years after introduction to the market. Other results seem counterintuitive, such

as a positive relationship between competitive density and first to market against the negative

relationship between competitive density and adoption of the innovation. This may be due to

first movers capturing the majority of the market share before competitors can respond, and

the late movers find it harder to attain market share.

The Share at most recent introduction shows that market leaders are often the first to

introduce incremental innovations to maintain their top spot. An incumbent firm gains long-

term market share advantages from number of times first to market, while industry entrants

with first to market innovations did not achieve any similar long term effects. Hypothesis 5 was

tested by adding the lag share variable and results were consistent with the hypothesis,

showing that introduction of incremental innovations does not decrease the likelihood of the

business dissolving. Hypothesis 6 is tested by adding the competition variable, and is confirmed

by the data which shows that the likelihood of a business shutting down increases as the

number of firms offering similar products increases.

Lead User R&D and Consumer Innovation:

Von Hippel (2005) investigates the effects of lead user driven R&D and innovation. He

cites his study from 2002, Lilien, Morrison, Searls, Sonnack and Von Hippel, which investigated

the difference between 5 lead user research projects and 42 non lead user projects by the

company 3M from February 1999 to May 2000. Results of this study can be found in Table 2.


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They show that lead user projects were significantly more novel ideas, addressed customer

needs more effectively, had higher probability of success, and most remarkably, the 5 lead user

concepts accounted for $146 million in sales whereas the 42 non lead user concepts accounted

for only $18 million in sales. Von Hippel also shows that users of many different products are

innovating on their own and freely distributing their innovations. He cites Luthje (2003) which

explored surgeons modifying their medical equipment in Germany. 262 surgeons responded to

the questionnaire and 22 percent of those respondents indicated that they had developed or

improved medical equipment on their own, and 48 percent of these innovations would soon be

marketed and released by manufacturers of medical equipment.

Von Hippel, de Jong, & Flowers (2011) is an investigation of the development and

modification of consumer products in the UK via a phone survey of 1,173 UK consumers. 6.1

percent of those surveyed say that they had created or modified products that they had used in

the last 3 years and spend an estimated 3.2 billion annually, which is nearly one and a half

times the R&D expenditures of all firms in the UK combined. 17% of the innovators surveyed

diffused their ideas to other people. More impressive was that 90 percent of respondents

reported developing their innovations entirely on their own. Only 2 percent of respondents

formally protected their innovations with intellectual property rights, showing that the

consumer innovators are willing to share their ideas and they think property rights protection

ineffective or too expensive. The conclusion of the article calls for policy makers to account for

consumer innovation in their countries and decrease costs of communication between

innovators and institute policies to encourage diffusion of innovation.


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Effects of regulation and R&D intensity on Innovation:

Ahn (2003) is a massive literature review on innovation. The main conclusions are that

competition enhancing policies cannot be measured with gains of efficiency in the short run,

network effects and positive feedback effects make competition fierce and increase innovation,

market concentration is not conducive to innovation (this contradicts the Anchor-Tenant

hypothesis highlighted later in this paper), and firm dynamics are an important part of

innovation and productivity growth.

Ahn cites Bound et al (1984) and Pavitt et al (1987) that show that both very large and

very small firms account for a large share of innovations. R&D intensity does not just increase

with size of firm, and some data in Bound et al (1984) show that productivity declines after R&D

increases to a certain level. This is shown in Graph 1, as patents per million R&D dollars

decreases as the size of R&D increases. A study of 16 OECD countries from 1980-1998

conducted by Guellec & de la Potterie (2001) showed that R&D increases multifactor

productivity, shown in Table 3. According to their regression, 1 period-lagged Foreign R&D

growth, 2 period-lagged Public R&D growth, 2 period-lagged Business R&D, and 3 period-lagged

Public R&D are all positively correlated with multifactor productivity. Ahn also cites Bassanini &

Ernst (2002) which found a negative correlation between R&D intensity and numbers of

domestic economic regulations and non-tariff barriers to trade. These results can be found in

Table 4, which illustrates that increasing regulation decreases R&D and thus innovation. This is

backed up by Olley and Pakes (1996) which found that productivity in the telecommunications

equipment industry saw significant increases in periods that decreased regulations.


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Anchor-Tenant Hypothesis:

Agrawal & Cockburn (2003) attempts to find support for the anchor-tenant hypothesis.

The anchor-tenant hypothesis is that a large, local, R&D intensive firm will enhance the regional

innovation system. They define an anchor-tenant as a firm that is heavily engaged in R&D and

has some sort of absorptive capacity in a technological area. The idea is that the anchor-tenants

will have significant positive externalities on smaller innovative firms. The data used were

indicators of academic research activity among a sample consisting of 259 census metropolitan

statistical areas (MSAs) in the US and Canada. Patent counts were used to measure industrial

R&D and publication counts were used to measure university research activity. Comparisons

between similar sized MSAs show the effects of anchor tenants.

Analysis descriptive statistics of the data shows that counts of patents and papers are

highly concentrated within a handful of MSAs, illustrated in Table 5. There are positive

correlations between papers and patents across MSAs, showing a positive statistical

relationship between levels of university research and levels of industrial R&D. Similar sized

MSAs, such as LA and NY, can be compared to show large differences in industry patent

numbers relative to the presence of anchor tenants, shown in Table 6. LA had 21 medical

imaging industry patents whereas NY had 43, and the NY MSA contained two anchor tenants,

IBM and Lucent Technologies, whereas LA had none. Similar comparisons could be seen with

Pittsburgh not having an anchor tenant and only getting 1 industry patent, while Rochester,

who has Eastman Kodak as an anchor tenant, received 34 industry patents over the same time

period.


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Agrawal & Cockburn then regress their ZIP (Zero-Inflated Poisson) model to find out the

relationship between the presence of an anchor tenant within an MSA and the number of

papers and patents coming from the MSAs, shown by Table 7. They find that for the three

technology areas they focused on (medical imaging, signal processing, neural networks) that

the coefficient on the interaction term between anchor tenants and papers are all positive and

strongly significant, showing that the presence of an anchor tenant has a direct effect on

numbers of papers published. To further test this hypothesis, Agrawal & Cockburn analyze a

locational Gini coefficient, which measures the extent to which the distribution of paper

publishing activity across geographical units strays from a uniform distribution. A Gini

coefficient score of 0 shows that academic research is evenly distributed via geographical units,

and a Gini coefficient score approaching .5 shows academic research that is highly concentrated

in a single geographical unit. Their results are shown in Table 8. The locational Gini coefficients

for all three technology areas are all above .4, which further backs up the hypothesis that

academic research is focused around highly centralized areas around anchor tenants.

Differences resulting from using multiple sources of R&D, including cooperative efforts:

Cassiman and Veugelers (2002) investigate complementarity between different

innovating activities using data from the Community Innovation Survey on Belgian

manufacturing firms. A sample of 445 innovative Belgian firms from 1993 was used for analysis.

The regressions analyze the differences in effectiveness of in-house R&D, purchased R&D, and

different combinations of the two. To summarize the data, 81 percent of the innovating firms

had their own internal R&D activities, 30 percent of firms had cooperative agreements with


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other firms, and 69 percent bought their R&D via external sources. 35 percent of firms both

made and bought their R&D, 27 percent of firms made, bought, and cooperated with other

firms for their R&D.

Cassiman & Veugelers then regress their independent variables:

SIZE (sales in 108

1992 Belgian Francs), EMPL (# employees in 1992 in units of

10), EXPINT (intensity of exports in 1992 exports/sales x 0.1), OBSTMARKET (scale of 1-5

on market importance of innovation), OBSTTECHNOLOGY (scale of 1-5 of importance of

lack of technological opportunities as barriers to innovation), PROTLEG (scale of 1-5 of

effectiveness of patent effectiveness), PROTSTRAT (scale of 1-5 of effectiveness of

secrecy as protection measure of innovation), PROTECTION (scale of 1-5 of effectiveness

of patents, copyrights, registrations of brands as measure of innovation), BASICRD

(importance for the innovation process of information from research institutes),

OBSTRESO (scale 1-5 importance of lack of innovation as barrier to innovation),

FREEINFO (importance of patents, conferences, publications as information sources for

innovation), COMPINFO (scale 1-5 importance of competitors as information sources for

innovation), Make&Buy R&D, MakeOnly, BuyOnly, NoMake&Buy, Make&Buy&Coop,

Make&Coop, Buy&Coop, and INDUSTRY DUMMIES against the independent variable

%SalesNewP (percentage of sales generated by new products within the past two

years).

EXPINT is the most highly correlated with a coefficient of .739, significant to the 5% level.

Make&Buy R&D increases sales 13.9 percent, significant to the 5% level. Make&Buy&Coop


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increased sales 12.6 percent, significant to the 10% level. They go on to do a multinomial logit

model, which shows that firm size positively affects all combinations of innovation activity.

They find that making and buying R&D increases product introductions by 7 percent, and if the

firms cooperate, the productivity increases even more. The data shows that small firms are

more successful with their innovations, and export-oriented firms are more productive via

innovation. The most productive firms are those that both make and buy their R&D, and

acquiring outside R&D significantly increases innovative performance only when the firm has

their own internal R&D. The results for their productivity regression and their multinomial logit

and bivariate probit models can be seen in Tables 9 and 10.

Sampson (2003) conducts similar research to that of Cassiman and Veugelers (2002),

while focusing on the telecommunications equipment industry. They use a sample of firm

patenting performance from 463 R&D alliances from the US, Japan, and Europe. The dependent

variable for regression analysis is Firm Innovative Performance (Post Patent). Dependent

variables are Technological Diversity and Organization, and control variables Pre-alliance Firm

Patents, Alliance Scope (Narrow, Intermediate, Broad), Multilateral Alliances, Prior Linkages,

Time of Alliance, Prior Alliance Experience, Other Concurrent Alliances, and International

Alliances. Sampson has two hypotheses that he intends to investigate:

H1: R&D alliances with moderate diversity contribute more to firm innovation than

alliances with very low or very high levels of capability diversity.


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H2: At higher levels of technological capability diversity, alliances organized by equity

joint venture contribute more to firm innovation than alliances organized by bilateral

contract. (Sampson 2003)

Through a negative binomial estimation model of firm patenting based on the described

independent variables without including alliance organization effects, Sampson finds that

Technological Diversity is positive and Technological Diversity2

is negative, shown in Table 11.

This shows that firm patents increase with Technological Diversity to a certain point, and then

the relationship becomes negative, illustrated in Figure 2. The effects of the alliance

organization on this relationship are illustrated in Figure 3.

Variations in Small Firms effectiveness in approaches to R&D:

Baldwin (1995) examines different strategies as determinants of success among small

and medium sized firms; management, human resource practices, marketing, financing, and

innovativeness of the firm. They find that innovation is the most important determinant of

success for a wide range of industries. The data came from a survey of firms with less than 500

employees and less than $100 million of assets in 1984. Only firms that had growth in

employment, assets, and sales between 1984 and 1988 were used for the sample to eliminate

declining firms. There were a total of 1,480 valid firms included in the survey, with average

sales of $6.6 million in 1989, average assets of $4.7 million, and an average employment of 44

people. 86 percent of the firms were independently owned and operated with the other 14

percent affiliated with a parent firm.


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The firms were asked to assess the importance relative to growth and competitiveness

of the various determinants of performance already listed on a scale of 0-5, with 0-N/A, 1-not

important, and 5-crucial. The results are shown in Figure 4, with the firms ranking management

skills, skilled labor, marketing capacity, and access to the market the highest, with mean scores

over 2.5. R&D is ranked second to last, just above 1.4. The firms were asked to rank their

sources of innovation, scoring customers, management, and their suppliers the highest, all

above 2.5. R&D was ranked near the bottom at 1.1, shown in Figure 5. Figure 6 shows the firms

self-assessed rank of their position compared to their competitors, with the highest mean

reported self-assessment scores between 3.5 and 4.0 for customer service, flexibility to

customers, and quality of product. The self-assessed mean score for R&D Spending was the

lowest at 1.4. Baldwin finds that the firms that were in the more-successful group had reported

a mean self-assessed score of R&D-innovation capability 41 percent higher than the less-

successful group, and a 33 percent higher score for R&D innovation spending. This shows that

for small and medium sized firms, R&D capability and spending are the most overlooked,

underappreciated, and undervalued sources of potential profits.

Effects of Venture Capital investment on R&D productivity:

Kortum & Lerner (1998) investigates the magnitude of venture capitals effect on

industrial innovation and R&D. They constructed a sample of 530 venture-backed and non-

venture-backed companies in Middlesex County, Massachusetts, spanning 20 industries from

1965-1992. They use regression analysis to determine the ratio of venture financing dollars to

private R&D expenditures, finding evidence that suggests a dollar of venture capital is as much


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Tables:

Source: Banbury & Mitchell 1995


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Source: Von Hippel 2005


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Source: Guellac & Potterie 2001


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Source: Bassanini & Ernst 2002


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Source: Agrawal & Cockburn 2003



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Source: Cassiman & Veugelers 2002


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Source: Cassiman & Veugelers 2002


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Source: Sampson 2003


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Source: Kortum & Lerner 2008


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Graphs:

Source: Bound et al 1984


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Source: Baldwin 1995


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References

Agrawal, Cockburn (2003) - The anchor tenant hypothesis: exploring the role of large, local,

R&D-intensive firms in regional innovation systems International Journal of Industrial

Organization Vol. 21, pg. 1227-1253

Ahn (2002) - Competition, innovation and productivity growth: a review of theory and

evidence OECD Economics Department Working Papers, No. 317, Jan 17

Baldwin (1995) - Innovation: The key to success in small firms Micro-Economic Studies and

Analysis Division, Statistics Canada and Canadian Institute for Advanced Research, Economic

Project Growth, February

Banbury, Mitchell (1995) - The effect of introducing important incremental innovations on

market share and business survivalStrategic Management Journal, Vol. 16, pg. 161-182

Bassanini, Ernst (2002) - Labour Market Institutions, Product Market Regulation, and

Innovation: Cross-Country Evidence, OECD Economics Department Working Papers, No. 316,

OECD Publishing.

Bound et al (1984)Who does R&D and who patents?, National Bureau of Economic

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Cassiman, Veugelers (2002)Complementarity in the Innovation Strategy: Internal R&D,

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Cierpicki, Wright, Sharp (2000)Managers knowledge of marketing principles: the case of

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pg 771-790

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