Peer reviewed business journal article

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Business Finance

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Webster University

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Need to separate 4 page papers, not including the title and reference pages... Abstract not required.

Week 5: Journal Article #3

Students will write a two-page summary of a peer reviewed business journal article. Please include a Title Page with a Running Head title, Centering Information (that includes a title, your name, and Webster University) for this assignment). The summary should thoroughly address each of the following:

  1. Title, Author (s), Journal, Date, Volume, Number, Pages.
  2. Introduction/Purpose. What basic question is the investigator trying to answer? Why?
  3. Method/Design
    1. What or who are the participants? What method is used to collect the research data? Is this a quantitative or qualitative study? Why?
    2. What task do they perform or what tests do they take, or what characteristics are measured?
  4. Results. What were the main findings in the study?
  5. Discussion. In general, what did the study demonstrate? What are the implications of study? What questions remain for further research?
  6. Criticisms. Point out at least two strengths and weaknesses in the research. Explain these criticisms thoroughly.
  7. Attach a copy of the peer reviewed business journal article you used for this assignment.

Your assignment must follow these formatting requirements:

  • Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
  • Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

Use the following template for the paper... APA_Template_With_Advice_(6th_Ed) .doc

Week 6: Journal Review #4

Students will write a two-page summary of a peer reviewed business journal article. Please include a Title Page with a Running Head title, Centering Information (that includes a title, your name, and Webster University) for this assignment). The summary should thoroughly address each of the following:

  1. Title, Author (s), Journal, Date, Volume, Number, Pages.
  2. Introduction. What basic question is the investigator trying to answer? Why?
  3. Method
    1. What or who are the participants?
    2. What task do they perform or what tests do they take, or what characteristics are measured?
  4. Results. What were the main findings in the study?
  5. Discussion. In general, what did the study demonstrate? What are the implications of study? What questions remain for further research?
  6. Criticisms. Point out at least two weaknesses in the research. Explain these criticisms thoroughly.
  7. Attach a copy of the peer reviewed business journal article you used for this assignment.

Your assignment must follow these formatting requirements:

  • Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
  • Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

Use the following template for the paper... APA_Template_With_Advice_(6th_Ed) .doc

Week 7: Journal Review #5

Students will write a two-page summary of a peer reviewed business journal article. Please include a Title Page with a Running Head title, Centering Information (that includes a title, your name, and Webster University) for this assignment). The summary should thoroughly address each of the following:

  1. Title, Author (s), Journal, Date, Volume, Number, Pages.
  2. Introduction. What basic question is the investigator trying to answer? Why?
  3. Method
    1. What or who are the participants?
    2. What task do they perform or what tests do they take, or what characteristics are measured?
  4. Results. What were the main findings in the study?
  5. Discussion. In general, what did the study demonstrate? What are the implications of study? What questions remain for further research?
  6. Criticisms. Point out at least two weaknesses in the research. Explain these criticisms thoroughly.
  7. Attach a copy of the peer reviewed business journal article you used for this assignment.

Your assignment must follow these formatting requirements:

  • Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
  • Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

Use the following template for the paper... APA_Template_With_Advice_(6th_Ed) .doc

Week 8: Journal Review #6

Students will write a two-page summary of a peer reviewed business journal article. Please include a Title Page with a Running Head title, Centering Information (that includes a title, your name, and Webster University) for this assignment). The summary should thoroughly address each of the following:

  1. Title, Author (s), Journal, Date, Volume, Number, Pages.
  2. Introduction. What basic question is the investigator trying to answer? Why?
  3. Method
    1. What or who are the participants?
    2. What task do they perform or what tests do they take, or what characteristics are measured?
  4. Results. What were the main findings in the study?
  5. Discussion. In general, what did the study demonstrate? What are the implications of study? What questions remain for further research?
  6. Criticisms. Point out at least two weaknesses in the research. Explain these criticisms thoroughly.
  7. Attach a copy of the peer reviewed business journal article you used for this assignment.

Your assignment must follow these formatting requirements:

  • Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
  • Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

Use the following template for the paper... APA_Template_With_Advice_(6th_Ed) .doc

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Explanation & Answer

Attached.

(Revised)

Innovation, Productivity and Growth in US Business Services:
a Firm-level Analysis

Mica Ariana Mansury and James H Love
Economics and Strategy Group
Aston Business School
Aston University
Birmingham B4 7ET
UK
Email: j.h.love@aston.ac.uk
Tel: 0121 204 3162

Abstract
This paper examines the impact of innovation on the performance of US business service
firms. We distinguish between different levels of innovation (new-to-market and newto-firm) in our analysis, and allow explicitly for sample selection issues. Reflecting the
literature which highlights the importance of external interaction in service innovation,
we pay particular attention to the role of external innovation linkages and their effect on
business performance. We find that the presence of service innovation and its extent has
a consistently positive effect on growth, but no effect on productivity. There is evidence
that the growth effect of innovation can be attributed, at least in part, to the external
linkages maintained by innovators in the process of innovation. External linkages have
an overwhelmingly positive effect on (innovator) firm performance, regardless of
whether innovation is measured as a discrete or continuous variable, and regardless of the
level of innovation considered.
Acknowledgements:
We are grateful for the constructive comments of Stephen Roper and two anonymous
referees.
Key words: Innovation, Services, External Linkages, Productivity, Growth

1. Introduction
In the last decade an increasing body of research has begun to examine the nature,
types, and causes of innovation in services. However, there is much less research on
the impact of service innovation on business performance, especially at the firm level.
As Cainelli et al (2006) point out, this is partly because of the difficulties involved in
obtaining micro-level data, which is well developed in manufacturing but less so in
services1, and partly because of methodological problems relating to the availability
of appropriate indicators to measure innovation activities in services. Metrics which
are standard in manufacturing, such as R&D and patents, may be less meaningful in
the case of services (Evangelista and Sirilli, 1995; Djellal and Gallouj, 1999; Love
and Mansury, 2007)
It is increasingly recognised that models of innovation developed principally for
manufacturing may not apply easily to services. For example, the traditional
distinction between product and process innovation is less useful in services, which
are often processes that cannot be easily disentangled from the outcomes they
produce. And the way in which service firms innovate are often different from
manufacturing firms. Tether (2005) analyses data from the European Innobarometer,
a telephone survey of managers in over 3,000 firm, and found substantial differences
in the way manufacturing and service firms performed innovation. Service firms
were much more likely to regard organisational change as important and to develop
innovations in collaboration with customers and suppliers, while manufacturers
tended to stress the importance of their in-house R&D and research links with
universities. In addition, manufacturers tended to emphasise ‘hard’ strengths such as
R&D competence and flexibility of production methods while service providers more
frequently stressed ‘soft’ skill such as workforce skills and collaborative interactions2.
An important issue is therefore whether and how the different ways in which service
firms perform the process of innovation affect the economic performance outcomes
which result from innovation. This is the focus of the present paper, which examines
1

This has been partly mitigated in Europe by the extending the coverage of the Community Innovation
Survey to provide more complete data on services.
2
See also Freel (2005) for an analysis of the differential links between innovation and skills among
manufacturing and service SMEs.

1

the impact of innovation on the economic performance of a sample of service sector
firms. The paper adds to our knowledge of service sector innovation in three ways.
First, we use data from the United States: most of the previous studies of the effects
of innovation in services have been from Europe (e.g. Cainelli et al , 2004, 2006).
Secondly, we distinguish between different levels of innovation (new-to-market and
new-to-firm) in our analysis, and allow explicitly for sample selection issues. Finally,
reflecting the literature which highlights the importance of external interaction in
service innovation (Howells and Tether, 2004; Tether, 2005; Kanerva et al, 2006), we
pay particular attention to the role of external innovation linkages and their effect on
business performance.

2. Service Innovation and Business Performance

Conceptualising Innovation in Services
Traditionally, services have been defined in a rather negative sense; once production
industries are defined, everything else is allocated to a tertiary ‘services’ sector. This
bundling of activities of heterogeneity in application and production has added to the
difficulties of understanding the most rapidly growing sector in modern economies
and has contributed to the tendency in the past to consider services as residual,
dependent on manufacturing, technologically backward, and – consequently – not
very innovative.
This view of services has now changed. Services are now often defined as activities
directed at creating changes or transformations of form, place or time of availability
in some entities, and the entities involved may be material objects, goods, people, the
natural environment or symbolic representations (data, text, etc.) (Metcalfe and Miles,
2000). While it is now generally accepted that service firms do innovate and that
frequently they also conduct R&D, the empirical evidence suggests that, on average,
innovation rates in services tend to be lower than those in manufacturing (e.g.
Kanerva et al, 2006)3. This has tended to suggest that, at least in part, the lower
levels of innovation in services arises because service firms innovate differently,
3

However, much of this information arises from analysis of data arising from the successive
Community Innovation Surveys (CIS2, 3 and 4): we know much less about the nature and effects of
innovation elsewhere.

2

which in turn has led to different ways of conceptualising innovation in services. For
example, Coombs and Miles (2000) distinguish three approaches to studying service
innovation: the assimilation approach, the demarcation approach, and the synthesis
approach.
(i)

The assimilation approach analyses services in the same way as
manufacturing, using technology-based indicators and metrics. Research via
this assimilation method may pose a limited perception of innovation,
especially with regard to technological innovation (Coombs and Miles, 2000;
Djellal and Gallouj, 2000; Drejer, 2004).

(ii)

The demarcation approach argues that service innovation is distinctively
different from innovation in manufacturing, following dynamics and
displaying features that require new theories and instruments (Sundbo and
Gallouj, 2000; Djellal and Gallouj, 2001),

(iii)

The synthesis approach suggests that while manufacturing and service
innovation share many similarities which allow them to be analysed together,
service innovation brings to the forefront hitherto neglected elements of
innovation that are of relevance for manufacturing as well as services e.g. the
great heterogeneity among services and the need to take a broad view of
innovation and the process which underlies it (Gallouj and Weinsten, 1997;
Preissl, 2000; Hipp and Grupp, 2005).

Consistent with both the demarcation and synthesis approaches is the recognition that
the process of innovation may be different in services; for example, the traditional
distinction between product and process innovation may be less meaningful in
services. Howells and Tether (2004) suggest a more meaningful distinction may be
between inward-looking and outward-looking innovation activity, with the former
dealing mainly with how the firm undertakes its activities (i.e. close to the process
issue, but with the potential for product effects), while outward-looking innovation is
more concerned with the firm’s interaction with other actors, notably customers. This
is supported by the view that the use of external sources may be particularly
important for the service sector. In a comparison of the innovation process of
3

manufacturing and service firms, Tether (2005) finds that while manufacturers are
more likely to innovate through using in-house R&D and collaborations with
universities and research institutes, service firms are more likely to make use of
collaborations with customers and suppliers, especially where they have an
organisational orientation to their innovation activities. Leiponen (2005) finds
support for this view. In a survey of Finnish business service firms, she finds that
external sourcing of knowledge, especially from customers and competitors,
positively affected both the probability and extent of innovation, while in-house R&D
intensity had no discernible effect.
In a recent contribution Kanerva et al (2006) also note the tendency for service firms
to be more outward focussed than manufacturing firms in terms of the use of external
knowledge sources in innovation. Examining CIS3 data in manufacturing and
services for all 25 EU member states, they conclude that innovation in the service
sector cannot easily be measured through indicators developed principally to measure
(technical) innovation in manufacturing, and conclude that the main reason for this is
because of differences in the nature of innovation in the service sector and in the
manufacturing sector. In particular, they argue that service sector innovation could
rely much less on the (internal) accumulation of capabilities, permitting service sector
firms to move much more rapidly to best practice than manufacturing firms.

Innovation and performance
Since the early work of Joseph Schumpeter (1934), innovation has been recognized as
a key element of competition and dynamic efficiency of markets. Innovators
(product, process and organizational) should take market share from non-innovators
and grow at their expense, until such time as the quasi-monopoly position is
undermined first by imitations of new products and processes, and ultimately by yet
newer products. In the long run, therefore, innovators will grow faster, be more
(dynamically) efficient, and ultimately be more profitable than non-innovators.
There is a wealth of evidence in the academic literature indicating a positive
relationship between innovation and firm performance in manufacturing (e.g. Crépon
et al, 1998; Lööf and Heshmati , 2001, 2002; Mairesse and Mohnen, 2003).
Reflecting the lack of maturity of the analysis of service sector innovation, studies of
4

the relationship between innovation and business performance in the service sector
are still relatively rare. Cainelli et al., (2004) note that much of the evidence in the
field is descriptive and not supported by robust evidence, especially at the firm level.
Much of what we do know about the link between innovation and performance in
services has come from the analysis of CIS data, especially in Italy. Cainelli et al.
(2004) match Italian CIS 2 data with longitudinal firm performance data, focussing
particularly on the relationship between innovation in the 1993-95 period with
economic performance in the subsequent three years (i.e. 1996-98). They find that
innovating firms consistently outperform non-innovators in terms of productivity and
growth, that a strong positive relationship exists between innovation and subsequent
productivity and growth, and that productivity is strongly linked to previous
investment in innovation activity. In a subsequent analysis of the same dataset,
Cainelli et al (2006) examine the interaction between innovation and performance in
more detail, and conclude that there is a two-way relationship: innovative firms
outperform non-innovators, but better performing firms are also more likely to
innovate, and to devote more of their resources to innovation. They conclude that
there is “a cumulative a self-reinforcing mechanism” linking innovation and
performance (p 454). Additionally, Evangelista and Savona (2003) report that service
firms which spend more on innovation per employee, and those introducing service
innovations, are more likely to report a positive impact of innovation on total
employment.
Although limited, the evidence on innovation and performance in services suggests a
positive effect of innovation on productivity and growth. There is therefore a body of
evidence suggesting that external linkages, especially customer linkages, have a
positive impact on innovation (Tether, 2005; Leiponen, 2005), and another body of
evidence indicating that innovation positively influences performance. The implicit
assumption, therefore, is that the performance impact of external linkages is entirely
indirect, via the impact on innovation. What is missing from the innovation literature
is any explicit consideration of the direct impact of external innovation linkages on
subsequent economic performance.

However, there is reason to believe such an

effect may exist. There is evidence (largely from the marketing literature) that firms

5

that are customer oriented4 experience an increase in performance (Narver and
Slater, 1990; Donaldson, 1993; Bougrain and Haudeville, 2002; Tether, 2002). In the
case of service firms, one key aspect of customer orientation is through integrating
the customer into the production and innovation process. It is not uncommon for a
service firm’s client to initiate and stimulate innovations, and frequently customer
participation is a necessary condition for success (Preissl, 2000). The close interaction
between service provider and customer participation comes in various forms while
creating service innovation, and numerous concepts have been developed in order to
account for this client participation, such as co-production, servuction and service
relationship (Sundbo and Gallouj, 2000): indeed, under some circumstance the
customer could become so closely involved with the innovation process as to be
virtually an internal rather than an external resource5.
Since other external linkages such as suppliers, consultants and subsidiaries can also
positively influence innovation (Love and Mansury, 2007), it is worth examining
whether these linkages too may have a direct effect on performance. In the empirical
estimation below we therefore first test whether there is any evidence of innovation
affecting performance on a sample of US business service companies, and then look
for evidence of a link between the extent of external involvement in innovation and
firm performance.

3. Data
Business services (classified as SIC 73) are defined by the US government as
establishments primarily engaged in providing services, not elsewhere classified, for
business establishments on a contract or fee basis. Data were collected via a postal
questionnaire which was mailed in 2004 to all US businesses listed under SIC 73 on
the Dunn & Bradstreet business database. The questionnaire collected information on
the firms’ innovative activity and performance over the previous three years, their
4

Rafiq and Ahmed (2000) define customer orientation as “A planned effort using a marketing-like
approach to overcome organizational resistance to change and to align, motivate and inter-functionally
co-ordinate and integrate employees towards the effective implementation of corporate and functional
strategies in order to deliver customer satisfaction through a process of creating motivated and
customer-oriented employees.”
5

We are grateful to an anonymous referee for making this point.

6

own R&D activity, and the extent of the involvement in their innovative activity of
six external linkages: strategic alliances or joint ventures, suppliers, subsidiaries,
customers, consultants, and competitors. With regard to new service introductions,
information on two ‘levels’ of innovation was obtained: new-to-market and new-tofirm (i.e. introduced by the firm for the first time but not new to the market). The
questionnaire was a modified version of that used in the Irish Innovation Panel (Love
and Roper, 2007) and was therefore compatible with the OECD Oslo Manual and
included most of the questions asked in the EU’s Community Innovation Survey, but
also included a number of questions relating to the firm’s commercial performance.
These included questions on turnover, capital investment and input costs, which
allowed calculations of value added, as well as employment and sales growth over the
period 2000-2003.
Following pilot testing, the questionnaire was administered by US mail, with a post
card reminder mailed nine days afterwards. Of the 3140 questionnaires mailed, 206
usable responses were obtained, representing a modest response rate of 6.5 %:
unfortunately, resource constraints prevented a further follow-up mailing. In
common with the population of SIC 73, the largest grouping of respondents comes
from computer services (32%), business services not elsewhere classified (20.4%)
and advertising (5.3%). No other sub-2-digit grouping represented more than 5% of
respondents, and despite the relatively low response rate the sub-sectoral distribution
of respondents is statistically representative of the Dunn & Bradstreet SIC 73
database (Table 1).
Almost 80% of respondents introduced at least one new service in the previous three
years, with an average of 41% of current sales being accounted for by services
introduced or improved within the previous three years, almost half of which was
represented by improvements to existing services. Table 2 shows descriptive
statistics for the economic performance and internal resource indicators of the sample,
split between innovators and non-innovators. Innovators have higher productivity
(value added per employee), sales growth and employment growth than noninnovators, providing prima facie support for the hypothesis that innovation is linked
to improved performance. However, innovators are also larger, more export oriented,
have a better-qualified workforce and are older than non-innovators. This clearly
7

suggests that these internal resource differences must be taken into account in
estimating the impact of innovation on performance, and also has implications for the
estimation procedure, outlined in the next section. The data on external linkages
show the importance of this source of knowledge and ideas for innovation in US
business services. The relevant question asks for the percentage of new services or
products deriving from suggestions and/or ideas from each of the six external sources.
Customers are, perhaps unsurprisingly, the single largest source of innovative ideas,
followed by strategic alliances, competitors and suppliers: consultants and
subsidiaries play a very minor role.
4. Model and Estimation
The empirical model relates the economic performance of US business services firms
to their innovation outputs and external linkages, conditioning for a set of internal
resource and other firm characteristics which may affect performance. The simplest
method of estimation would be to assume that the innovation decision and the extent
of innovation is simply exogenous to performance i.e.
PERFi = α + β0 Ri + β1 C i + β2 I i +ε i

(1)

Where PERFi is the performance of firm i, (value added per employee, sales growth,
employment growth) expressed in log form, Ri is a set of internal resource indicators,
Ci is a set of other firm characteristics, Ii is a measure of innovation.
However, both conceptually and given the data descriptions discussed above, it is
unreasonable to assume that innovators and non-innovators are randomly sampled
from the population of business services firms, and so allowance must be made for
the potential sample selection issues which this entails. For example, we have to
acknowledge the possibility that highly productive, high-growth firms self-select to
become innovators: if such self-selection is present this could seriously bias the
results of estimating equation (1). An obvious solution is the Heckman two-stage
estimator for sample selection. This procedure starts with a probit model of the
determinants of innovation, where the dependent variable is a dummy variable [0, 1]
indicating whether or not the firm has innovated over the previous three years. In the

8

second stage an equation such as (1) is estimated, but using the predicted values of
innovating derived from the probit equation. This can be expressed as follows:
PERFi = α + β0 Ri + β1 C i + β2 I i +ε i
I*i = γX + μ

(2a)
(2b)

Ii =1 if I*i >0, and Ii = 0 if I*i =0
Where I*i is a dummy innovation variable and X is a vector of determinants of
innovation. In the above case, because Ii is both the sample selection criterion and a
regressor in the second stage of estimation, a variation on the selection model such as
the treatment effects model is more appropriate. To allow for correlation between Ii
and εi equations (2a) and (2b) are estimated using 2SLS, using the predicted
probabilities from probit equation (2b) as the instrument for Ii (Greene, 1998, 716-7).
A variation on the basic model allows the measure of innovation in equation (2a) to
be the extent of innovation rather than a dummy innovation variable, measured by the
percentage of new-to-market or new-to-firm products in total sales. Here the standard
Heckman two-stage procedure can be used, preserving all observations in the second
stage.
The basic model implied by equation (2) does not allow for the process by which
firms gather knowledge for innovation, an issue which the literature reviewed above
indicates is particularly important for service sector firms. At the level of the firm,
conceptual models typically see external knowledge sourcing as a substitute for
internal knowledge creation (i.e. the classic make or buy decision) giving firms the
ability to obtain specialist knowledge and/or accelerate knowledge acquisition. Such
alternatives have, until recently, however, only been poorly reflected in the empirical
literature with Crépon et al. (1998) and Lööf and Heshmati (2001, 2002) implicitly
assuming that undertaking R&D provides a unique route through which a firm may
acquire the knowledge on which to base its innovation activities. This assumption is
contradicted by much recent evidence, however, which stresses the importance for
innovation of knowledge flows which span the boundaries of individual businesses
creating 'extended enterprises' and providing the basis for competition between
supply chains. At the level of the individual business too, inter-company networks

9

(e.g. Oerlemans et al., 1998) and intra-group knowledge transfers (e.g. Love and
Roper, 2001) have been shown to have positive effects on innovation outputs.
In order to allow for the influence of external knowledge sources operating on
performance through their interaction with innovation, the basic model is modified as
follows:
PERFi = α + β0 Ri + β1 C i + Σ β3 Ii.E i +μ I

(3a)

I*i = γX + μ

(3b)

Ii =1 if I*i >0, and Ii = 0 if I*i =0
where Ii.E i represents the interaction between innovation and six forms of external
knowledge sources. Because Ii does not appear directly as a regressor in the second
stage, estimation of equation (3) can be carried out using the standard Heckman twostage procedure, preserving all observations in the second stage. As with equation
(2), three innovation metrics are employed: a dummy innovation variable, the
percentage of new-to-market products in total sales, and the percentage of new-tofirm products in total sales.
In the estimations discussed below, performance is measured in three ways.
Productivity is measured by value added per employee in 2003, while growth is
measured by the percentage change in sales volume and employment over the period
2000-2003. All estimations are carried out with the dependent variables in logged
form.
An important element in the two-stage modelling process is equation (2b), and an
appropriate vector X, the determinants of whether or not firm i undertakes service
innovation. Here we employ a model in which innovation depends on the firm’s
internal knowledge generation (i.e. R&D) and external knowledge linkages, as well as
indicators of other internal resources such as size, human capital and ownership
structure. This model is detailed in Love and Mansury (2007) where it is shown to
have a very good fit with the data and strong predictive properties. The model results
are shown in the Appendix (Table AII).

10

5. Results
Innovation and performance
Table 3 shows the results of estimating equation (2a). Employment shows a Ushaped relationship with growth, but has no effect on productivity. As might be
anticipated, capital intensity is positively associated with productivity, while
exporting firms are more productive but grow more slowly than non-exporters. The
only pertinent finding under ‘other service firm characteristics’ involves offerings
tailored to specific customer groups. This finding suggests that service firms which
offer tailored service and product have more sales growth: possible reasons for such
sales growth may include niche marketing or an expansion of offering newly tailored
services and products to existing customers.
The key finding from Table 3 is the effect of innovation. Innovation has a positive
effect on sales and employment growth, a finding valid for both the dummy variable
and continuous measures of innovation6. Estimated at the mean value of each, the
results for sales growth indicate elasticities of 0.20 for new-to-market products and
0.39 for new-to-firm products, suggesting substantial growth effects of introducing
products which are new, even if they are not completely new to the market.
Innovation has no effect on productivity: intriguingly, the extent of both new-tomarket and new-to-firm products have negative (but insignificant) coefficients with
respect to productivity. Similar – and indeed stronger – effects have been noted in
studies of manufacturing industry. For example, in a study based on data from Ireland
Roper et al (2006) find that process innovation has no effect on productivity and
product innovation actually reduces productivity. This result, which has been noted
elsewhere (Freel and Robson, 2004), they interpret as a disruption effect: the
introduction of new products to a plant may disrupt production and reduce
productivity in the short term. Alternatively, the negative productivity effect of
innovation success may be explained by a product-lifecycle type effect. In this
scenario, newly introduced products are initially produced inefficiently with negative
productivity consequences before becoming established and the focus of process
innovations to improve productive efficiency. Leiponen (2000) also notes the negative

6

The employment effect of new-to-market innovations is just insignificant at 10%.

11

effect of product innovation on Finnish manufacturing firms’ profitability, which she
also ascribes to a disruption effect. The lack of significance of innovation’s effect on
productivity in the present sample suggests that any disruption effects were
insufficiently strong to cause actual decreases in productivity.
Table 3 also shows for each equation the inverse Mill’s ratio (Lambda), a significant
coefficient on which indicates the presence of a significant sample selection effect. In
only one case (the impact of new-to-market innovation on productivity) is there a
marginally positive lambda coefficient on the Heckman sample selection estimations,
suggesting that sample selection issues do not result in a substantial bias in the
estimation results.

Innovation, external linkages and performance
Table 4 shows the results of estimating equation (3a). Here the innovation variables
are interacted with the extent to which external actors were involved in the innovation
process (see Appendix Table AI). The interaction coefficients thus show the impact
on productivity and growth of external innovation linkages among innovators. In the
first set of estimations (columns 1-3) the interaction is with a service innovation
dummy; in the remaining columns external involvement is interacted with the extent
of new-to-market and new-to-firm product sales respectively. In all cases for noninnovators the interaction terms take the value zero.
The internal resource and firm characteristic indicators show virtually no difference
with those of Table 3. The employment, capital intensity and export effects remain
unchanged; the only slight difference is that the effect of tailored services disappears.
However, there is substantial new information provided by the innovation interaction
terms. The first point to note is that, where they have an effect, external innovation
linkages are overwhelmingly positive: of sixteen significant interaction coefficients
all but two are positive, suggesting that external innovation linkages have a generally
positive effect on the performance of US business service firms. This is particularly
true of links with alliance or joint venture partners and with customers. The greater
are linkages with alliance partners, the higher is sales and (generally) employment
growth across all types of innovation. The greater are customer linkages among
12

innovators the higher is sales and employment growth. Involvement with external
consultants in innovation leads to higher productivity but no effect on sales or
employment growth. The one negative effect is with respect to suppliers, where
greater supplier linkages are associated with reduced growth rates. The coefficients
are negative in most cases here, but significant only in the case of new-to-market
innovation linkages. As with most of the estimates in Table 2, the insignificant
coefficients on the inverse Mill’s ratio (lambda) suggest no sample selection bias in
the estimation.
Because of the log-linear nature of the estimation, some idea of the scale of the
external interaction effects can be gained by calculating the elasticities of significant
coefficients at their mean value: these are shown in Table 5. Because of the nature of
the interaction terms little significance can be attached to size of the elasticities per
se, but we can make inferences of which type of external interactions have relatively
greater effects. In terms of sales and employment growth it is clear that customer
innovation linkages have the greatest effect, approximately double those of
alliance/JV innovation interaction. The negative elasticities of new-to-market
customer linkages on growth are very small, albeit statistically significant. In all
cases differences in how the interaction term is measured makes relatively little
difference to the size of the elasticities: for example, the elasticities for customer
involvement on sales growth are 0.29, 0.24, and 0.28 respectively. This similarity in
elasticities is also the case for linkages with consultancy firms, the only external link
that has any effect on productivity,

6. Conclusions
The purpose of this analysis is to add to the relatively limited body of research on the
impact of innovation on service sector performance. Previous research suggests a
positive relationship between innovation, productivity and growth in manufacturing,
but there is limited evidence for services and an apparent dearth of studies on US
services. The study has paid particular attention to the role of external linkages and
the way in which they interact with innovation to affect performance.
Using data from a survey of 206 US business services firms, we find that the presence
of service innovation and its extent has a consistently positive effect on growth, but
13

no effect on productivity. There is evidence that the growth effect of innovation can
be attributed, at least in part, to the external linkages maintained by innovators in the
process of innovation. External linkages have an overwhelmingly positive effect on
(innovator) firm performance, regardless of whether innovation is measured as a
discrete or continuous variable, and regardless of the level of innovation considered.
In particular, involvement with customers and alliance or joint venture partners in the
innovation process has a consistently positive effect on growth, while there is some
evidence that involving external consultants in the innovation process induces a
positive impact of innovation on productivity.
The obvious limitation of the study is its cross-sectional nature, with the implications
for endogeneity and direction of causality which this implies: does innovation really
improve performance, or are well-performing firms simply more likely to become
innovators? Within the confines of a cross-sectional study we have attempted to deal
with this issue; the structure of the questionnaire allows for a slight lagged effect of
innovation on performance, and we have explicitly allowed for sample selection
issues by using instrumental variable estimation. However, we are clearly precluded
from a detailed consideration of, for example, the lagged effect of performance both
on itself and on innovation. Notwithstanding this important issue, one of the clear
messages of this research is the important positive influence of external innovation
links on performance, coupled with the relatively slight influence of internal resource
indicators such as size and workforce qualifications. This may lend support for the
argument of Kanerva et al (2006) that the nature of innovation in the service sector
relies less on the stock of accumulated capabilities which e.g. R&D and patenting
activity provides in manufacturing, providing more leeway in services to use external
innovation linkages as a method of rapidly moving towards best practice. This may
in turn have implications for the conceptualisation of innovation in services, lending
further support for a demarcation or synthesis approach. Such an approach would not
only takes a broad view of innovation and the process which underlies it, but would
also allow both for the different ways in which innovation occurs in manufacturing
and services, and for the effect which these differences have on subsequent economic
performance.

14

Table 1. Sub-sectoral Distribution of Population and Sample

Main sub-sectors
Computer Services
Business Services NEC
Advertising Services
Other
Total

Dunn &
Bradstreet
(% firms)

Responses
(% firms)

27.9
15.9
8.2
47.9

32.0
19.9
7.8
40.3

100

100

2 (3 df)
p-value

6.01
0.111

Table 2. Descriptive and Performance Indicators: Innovators and
Non-innovators

Performance
Productivity ($ log)
Sales growth (%)
Employment growth (%)
Internal Resource Indicators
Employment
Exports (% of sales)
Capital intensity ($000)
Degree level employees (%)
Age (years)
Independent (proportion)
External linkages
Alliances/JVs (% of innovations)
Suppliers (% of innovations)
Subsidiaries (% of innovations)
Customers (% of innovations)
Consultants (% of innovations)
Competitors (% of innovations)

Innovators
(mean)

Non-Innovators
(mean)

11.2
40.3
20.9

10.7
14.3
11.5

16918
14.1
210.4
43.6
40.5
0.55

1151
9.5
121.5
27.9
20.5
0.74

16.8
10.1
4.9
29.0
5.8
13.2

-------

All differences except c...


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