Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Learning orientation, innovativeness and financial
performance in traditional manufacturing firms: a higherorder structural equation model
Erlend Nybakk
Norwegian Forest and Landscape Institute, Pb 115, NO-1431 AAs, Norway.
Tel: +4764949099. E-mail: [email protected]
Abstract
This study examines the relationships among learning orientation, firm innovativeness and financial
performance in the context of the Norwegian wood industry. A questionnaire-based survey was sent to the
CEOs of firms in the wood industry in Norway (241 usable replies, response rate of 49 percent). Learning
orientation and firm innovativeness were conceptualised and analysed as latent second-order constructs
using structural equation modelling. The findings show that learning orientation has a positive effect on
firm innovativeness in the traditional manufacturing industry. In addition, learning orientation was found
to positively affect financial performance via the full mediating effect of firm innovativeness.
Furthermore, firm innovativeness was also found to have an independent positive effect on financial
performance. No direct effect of learning orientation on financial performance was found. According to
the data, firm age also does not appear to affect the relationship between learning orientation and firm
innovativeness.
Keywords Learning orientation, learning commitment, shared vision, open-mindedness, intraorganisational knowledge sharing, innovation, innovativeness, traditional manufacturing firms, wood
industry.
Electronic version of an article published as [International Journal of innovation
management, Volume 16, Issue 5, 2012, 28pp] [DOI No: 10.1142/S1363919612003873]
©[copyright World Scientific Publishing Company] [http://www.worldscinet.com/ijim/]
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
1 Introduction
Over the past several decades, scholars have increasingly focused on innovation as a key factor in
the creation of firms’ sustainable competitive advantages. Many researchers have found evidence
for a relationship between innovativeness and performance (Damanpour et al., 1989; Hurley and
Hult, 1998; Narver and Slater, 1990; Sinkula et al., 1997). Researchers have frequently
mentioned learning orientation as one of the antecedents of innovativeness (Calantone et al.,
2002; Slater, 1995; Wang, 2008). In addition, learning orientation is important for a firm’s
competitive advantage (Sinkula et al., 1997), and the literature has generally focused on the
effects of learning orientation on financial performance (Wang, 2008). Recently, however, the
focus has widened to include innovativeness as a mediating factor (Akgün et al., 2007; AragónCorrea et al., 2007; Keskin, 2006; Rhee et al., 2009). Other researchers have found that learning
orientation affects performance and that innovativeness is a mediating factor that also directly
affects performance (Calantone et al., 2002; García-Morales et al., 2007). Lloréns Montes et al.
(2005) found that organisational learning influences the administrative and technical innovation
gap as well as performance, but they also discovered that organisational learning has a direct
effect on performance. In summary, the literature is inconsistent in terms of whether
innovativeness plays a partial or full mediating role in the relationship between learning
orientation and firm performance.
This study examines the relationships among learning orientation, firm innovativeness and
financial performance in the context of traditional manufacturing firms. The moderating effect of
firm age was also tested. In the present study, learning orientation is defined as a firm’s degree of
commitment to learning, shared vision, open-mindedness and intra-organisational knowledge
sharing. Firm innovativeness is defined as the degree to which a firm creates and/or adopts new
products, manufacturing processes and business systems. Financial performance is defined as a
firm’s key measure of financial success over time, such as return on sales and overall
competitiveness.
The majority of studies on the relationships among learning orientation, firm innovativeness and
financial performance have ignored the direct effect of learning orientation on financial
performance (see e.g., Hult et al., 2004; Rhee et al., 2009). Additionally, many studies have
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
failed to test the significance level of the indirect effect, which is necessary to determine the total
effect of learning orientation on financial performance. Furthermore, this approach does not
clarify whether innovativeness has a partial or full mediating effect. This study seeks to fill this
gap with a higher-order structural equation model and bootstrapping to determine whether the
mediating effect of learning orientation is non-significant, partial or full (in addition to
determining the total effect).
Despite the large body of literature examining the relationship between learning orientation and
firm innovativeness, scholars have yet to thoroughly investigate many areas and industries. Many
studies have addressed specific contexts, such as companies in the USA with sales over $100
million (Hult et al., 2004), technology-intensive and innovation-oriented South Korean smalland medium-sized enterprises (SMEs) (Rhee et al., 2009), SMEs in Turkey (Keskin, 2006) and
the hotel industry in Indonesia (Nasution et al., 2010). In another related study, Calantone (2002)
examined technology companies in the USA that were large enough to have their own R&D
programs. The results of these empirical studies may not be applicable to the traditional European
manufacturing industry, which has received less scrutiny in this context (Becheikh et al., 2006).
In addition, many of the studies mentioned above are cross-sectional; they examine a specific
point in time and may be limited by survivorship bias. In other words, they are biased upwards
and run the risk of overstating the impact of learning orientation on firm innovativeness and
financial performance because the impact of learning orientation may be lower among firms that
have gone out of business. Thus, researchers should conduct studies on this issue in a more
homogeneous context. Additionally, as Calantone et al. (2002) emphasised, cross-national studies
are important. Accordingly, this study investigates the relationships among learning orientation,
firm innovativeness and financial performance in the context of the Norwegian wood industry,
which is a relatively homogeneous and traditional industry (Sande, 2008).
A large part of the literature on learning orientation and firm innovativeness does not account for
important dimensions of firm innovativeness. The shallow operationalisation of firm
innovativeness that is frequently used does not account for dimensions such as products,
processes, markets and organisation innovativeness. For example, a company may be innovative
at improving processes to reduce costs but not innovative at introducing new products to new
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
markets. If the aim is to build new knowledge in a new field, a basic operationalisation of firm
innovativeness can be advantageous. However, these results must be validated by a more in-depth
operationalisation of the term based on a long history of innovation research. Furthermore, prior
researchers have emphasised that a universal and reliable scale for measuring innovativeness
does not yet exist in the literature (e.g., Deshpande and Farley (2004). A clear definition of
innovativeness and the creation of a reliable, robust and valid scale to measure innovativeness are
necessary to build new knowledge in the field through survey-based studies. This study seeks to
fill this gap by utilising a broad definition of firm innovativeness and a second-order construct
evaluated via three first-order indicators: product, process and business system innovativeness.
In summary, this study investigated whether and to what degree learning orientation affects
financial performance both directly and through the mediation of firm innovativeness. A higherorder structural equation model and bootstrapping were used to determine whether the mediating
effect of learning orientation is non-significant, partial or full. Additionally, the moderating
effects of firm age on the direct relationships between learning orientation and firm
innovativeness and between learning orientation and financial performance were investigated.
The hypotheses presented in this paper were developed based on the questions mentioned above.
The remainder of the paper presents information on the theoretical background for the research,
followed by the method, analyses, results, discussion, implications and limitations of the study.
2 Theoretical background and hypotheses
2.1 Innovativeness and learning orientation
Although there are various definitions of innovation and innovativeness in the literature (Garcia
and Calantone, 2002), this study defines firm innovativeness as the propensity of firms to create
and/or adopt new products, manufacturing processes and business systems. Thus, the focus is on
products, processes and business systems that are new to a firm but not necessarily new to the
market. Accordingly, firm innovativeness includes both adoption and more radical innovations.
Product innovation includes the development of new products, improvements to existing products
and the adoption of products and is widely recognised as an important factor for manufacturing
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
firms (Cooper, 1999; Cormican and O'Sullivan, 2004; March-Chordà et al., 2002; Wheelwright
and Clark, 1992). Product innovativeness is frequently defined as a product’s level of newness in
relation to the firm and the market (Song and Montoya-Weiss, 1998).
One of the relevant processes involves the production process. Process innovativeness is defined
as the action that leads to process innovation and as the process itself (i.e., the technologies and
improvements used in production) that constitutes the innovation (Tatikonda and MontoyaWeiss, 2001). The process must be new, improved or newly adopted to be innovative. Business
system innovativeness can apply to every aspect of the firm that is necessary to manage,
structure, operate and administer the business and its internal and external environments.
Innovation in business systems includes organisational innovations (defined as the creation or
adoption of ideas or behaviours new to the organisation) and the use of new managerial and
working concepts and practices (Damanpour, 1987, 1996; Damanpour and Evan, 1984).
Wang (2008) conceptualises learning orientation as those firm values that influence a firm’s
approach to acquiring information. They emphasise the importance of planned processes in
allowing firm learning to lead to the achievement of common organisational goals. Other scholars
take a strict approach and claim that for meaningful learning to occur, learning must result in a
behavioural change (Fiol and Lyles, 1985; Garvin, 1993). In contrast, Hurley and Hult (1998),
Huber (1991) and Slater and Narver (1995) argue that the new knowledge a company acquires
will create the potential for the firm’s values to influence its behaviour. Thus, they do not require
an actual change in behaviour.
In this study, a learning organisation is defined as an organisation with a learning orientation.
Following Calantone (2002), this study defines a firm with a learning orientation as a firm that
creates and uses knowledge to obtain a competitive advantage, especially if the process involves
strategic planning and is executed across the whole organisation. Furthermore, in accordance
with Calantone et al. (2002), the term learning orientation is defined as a firm’s commitment to
learning, shared vision, open-mindedness and intra-organisational knowledge sharing. A learning
orientation helps a firm to acquire, disseminate and share information (Wang, 2008). Tidd (1997)
argued that organisations focused on learning can achieve a better understanding of the
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
organisational factors that affect the acquisition of new knowledge related to technology and the
market.
2.2 Frameworks and hypotheses
In this study, learning orientation is a higher-order construct comprising the following variables:
commitment to learning, shared vision, open-mindedness and intra-organisational knowledge
sharing. Firm innovativeness is a higher-order construct consisting of the following variables:
product innovation, process innovation and business system innovation. Financial performance is
a first-order construct. The conceptualised model hypothesises that learning orientation will have
a positive effect on financial performance both directly and through the mediation of firm
innovativeness. Firm age is expected to act as a moderating factor that enhances the effect of
learning orientation on firm innovativeness and the effect of learning orientation on financial
performance.
Figure 1
Theoretical framework of the study showing the study’s six hypotheses
Dotted line = hypothesised indirect positive effect
Solid line = hypothesised direct positive effect.
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
2.2.1 Direct effect of learning orientation on financial performance (H1)
Learning orientation is thought to be important for the development of competitive advantage
and the improvement of financial performance over time (Fiol and Lyles, 1985; Garvin, 1993;
Kropp et al., 2006; Sinkula, 1994; Slater, 1995). Calantone et al. (2002) found a direct link
between learning orientation and financial performance, and Senge (1990) claimed that for
learning to positively affect performance, a firm has to engage strategically in the field of
learning.
A firm’s learning orientation will help the firm to use information from its customers to improve
its products and services, increase its sales and maintain a larger customer base. The learning
orientation can also increase the firm’s knowledge base and enable it to utilise its resources more
effectively.
For example, in traditional manufacturing firms, knowledge about raw materials and technical
knowledge about machinery can be critical to performance. A firm’s ability to acquire and apply
this knowledge to its operations is a cornerstone of its learning orientation (Garvin, 1993). A
larger knowledge base achieved through continuous learning processes will also render the firm a
more attractive collaborator to its competitors, suppliers and customers. For example, a sawmill
and wood supplier is attractive if it has a high degree of fundamental knowledge about how to use
wood. Furthermore, for a firm to improve its performance over time, the firm must learn to
understand and satisfy its customers’ demands (Day, 1994; Narver and Slater, 1990).
Additionally, a firm with a learning orientation will typically monitor its competitors’ behaviours
in the market (Gatignon and Xuereb, 1997) to understand and learn from their strengths and
weaknesses (Calantone et al., 2002; Lant and Montgomery, 1987).
Firms with a learning orientation can achieve higher levels of strategic capability (GarcíaMorales et al., 2007), which allows them to build long-lasting competitive advantages (Sinkula et
al., 1997). Such firms tend to be more perceptive and better at coping with significant
environmental changes (Day, 1994). However, the learning orientation must be implemented
properly. For example, Garcia-Morales et al. (2007) emphasised that although the knowledge
shared among employees can result in a learning orientation (and thus in a higher financial
performance), errors can occur during the knowledge-sharing process, with negative
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
consequences for a firm’s overall profits. Regardless of the potential errors and time lags, this
line of reasoning supports the following hypothesis:
H1: A higher level of learning orientation will have a direct positive effect on a firm’s
financial performance.
2.2.2 The indirect effect of learning orientation on financial performance via
firm innovativeness (H4)
Learning orientation is thought to be an important antecedent of firm innovativeness or
innovation capacity (Alegre and Chiva, 2008; Calantone et al., 2002; Damanpour, 1991; Liao et
al., 2008). Scholars have argued that both learning orientation and market orientation are
important antecedents of firm innovativeness (Hurley and Hult, 1998; Lin et al., 2008; Rhee et al.,
2010; Sinkula, 1994; Slater, 1995). Several researchers have viewed learning orientation as a
mediator in the relationship between market orientation and firm innovativeness (e.g. Lin et al.,
2008). Others have emphasised the importance of employee creativity to innovation and
competitive advantage (Amabile, 1988, 1996; Hirst et al., 2009). Akgün et al. (2007) found that a
firm’s emotional capacity has a positive effect on its learning capability and product innovation.
They argued that a firm’s emotional capability helps it to focus its employees on new product
development and firm innovativeness.
Clearly, most empirical research on the relationship between learning orientation and firm
innovativeness is conducted on large firms (Keskin, 2006), which have more of the resources
needed for innovation and can take on a larger degree of risk because they can diversify their risk
by linking it to various activities throughout the firms (McDade et al., 2002). However, others
have argued that small firms exhibit relatively more innovation per employee (Acs and
Audretsch, 1990). Smaller firms have other advantages, such as a less extensive bureaucracy
(Thompson, 1969), and can access resources by collaborating with other actors (Ahuja, 2000).
Furthermore, one line of empirical studies has shown the importance of learning orientation to
firm innovativeness among SMEs (e.g. Chaston et al., 2001; Keskin, 2006).
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
The literature has also thoroughly debated the relationship between firm innovativeness and
financial performance. Countless studies have been performed in different fields to investigate
the relationships between firm innovativeness and financial performance (e.g. Calantone et al.,
2002; Deshpandé and Farley, 2004; Kohli and Jaworski, 1990; Narver and Slater, 1990; Rhee et
al., 2010) and between innovation and financial performance (e.g. Damanpour et al., 1989;
García-Morales et al., 2007; Hurley and Hult, 1998). Akgün et al. (2007) found a positive
relationship between product innovativeness and financial performance. West and Farr (1989)
emphasise that although innovations are expected to create benefits, the benefits will vary and
might not accrue at all. Uncertainty is inherent to innovation, which involves risk, and a positive
outcome is not guaranteed. Some researchers have shown that innovation does not necessarily
lead to improved financial performance (Cooper, 2001). However, the majority of researchers
claim that innovation and firm innovativeness are the key components of firm success (Hult et al.,
2004) and that the innovations that allow a firm to achieve a competitive advantage will
contribute to its financial performance (Damanpour, 1991).
Based on the literature examining the effect of learning orientation on firm innovativeness and
the effect of firm innovativeness on financial performance, one can logically assume that
learning orientation will have an indirect positive impact on financial performance via firm
innovativeness. Understanding how firms’ learning orientations indirectly affect financial
performance via firm innovativeness is complex. However, this conclusion is supported by the
findings of empirical studies. Garcia-Morales et al. (2007) studied farming, manufacturing,
construction and service firms in Spain and found that learning orientation both directly and
indirectly affects the financial performances of large firms and SMEs through innovation. A
continuous learning process that creates new knowledge and builds and maintains a knowledge
base is also a cornerstone of innovation activity (García-Morales et al., 2007). Both the
knowledge base itself and the process of knowledge creation are important to innovation. Cohen
and Levinthal (1990) have argued that a firm’s ability to recognise the value of new external
knowledge and to adapt and apply this knowledge to the business is critical to the firm’s
innovation capabilities. Because highly learning-oriented firms tend to make better use of the
information available to them, they are more likely to be innovative. If knowledge circulates and
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
creates firm innovativeness, a firm’s capacity to innovate may be enhanced and thus improve its
financial performance. This idea yields the following hypotheses:
H2: A higher level of learning orientation in firms leads to greater firm innovativeness.
H3: Greater firm innovativeness leads to better financial performance.
H4: Learning orientation will positively influence financial performance in an indirect
manner via firm innovativeness.
2.2.3 Age as a moderating effect (H5 and H6)
The age of an organisation is thought to moderate the effect of learning orientation (Calantone et
al., 2002; Sinkula, 1994). The ideas and information needed for innovation are often found
outside of the organisation (Jenssen and Nybakk, 2009), and information is gathered through
many different channels, including customers, suppliers and distributors. It takes time to build
strong relationships with customers and suppliers. Hence, older organisations have an advantage
over younger ones because the former have had more time to build the relationships that allow
them to obtain market information more efficiently. Therefore, Sinkula (1994) claims that older
firms have better access to information than younger firms. Older organisations also have had
more time to build efficient systems to gather and share information (Lukas et al., 1996).
Moreover, older organisations have accumulated more knowledge in selecting and employing
information. If the above statements hold, then the firm innovativeness and financial performance
of an organisation with a high level of learning orientation will improve as it grows older
(Calantone et al., 2002). This reasoning supports the following hypotheses:
H5: The older the organisation is, the stronger the relationship between learning orientation
and firm innovativeness.
H6: The older the organisation is, the stronger the relationship between learning orientation
and financial performance.
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
3 Methods
3.1 Empirical setting – the wood industry
This paper addresses the relationship between learning orientation, firm innovativeness and
financial performance within the Norwegian wood industry. Specifically, the study includes
sawmills, planning mills, laminated wood factories, furnishing and wood-product producers,
producers of paper, cellulose and wood pulp, and fibreboard firms. There were several reasons
why we selected this context. In doing so, we sought to validate previous findings by studying a
traditional manufacturing industry with well-established traditions, and the wood industry meets
these requirements (Sande, 2008). According to Jakobsen et al. (2001), the Norwegian wood
industry has exhibited a low growth rate relative to that of other industries. The sector’s
economic growth has been steadily sinking and its profitability has been lower than that of other
sectors. Through analyses of the business environment in the forest and timber trades, Jakobsen
et al. (2001) identified four main problems: 1) isolation, which hinders the transfer of knowledge
and stimuli; 2) low levels of competence at utilising market opportunities and research, and the
results of commercial development; 3) little direct contact with international markets; and 4)
weak pressure on innovation. Most firms in the industry are also in a mature phase of their lifecycle (Sande, 2008).
By choosing a traditional, homogeneous industry in Norway, one have ensured a certain
isolation of the study and minimal variation in unknown variables (Sande, 2008). However, it
was also important to ensure adequate variation in the variable. The Norwegian wood industry
fulfils both demands because it typically uses the same raw materials and has the same end
market (the building products market) (Sande, 2008). At the same time, it is an industry that is
comprised of a variety of firms that produce many different products from simple components to
complicated products such as furniture and stairs.
3.2 Study design and questionnaire development
This study was conducted using mail surveys in conjunction with theories regarding causal
connections. Higher-level constructs are represented by empirically observed variables. The
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
models consist of several hypotheses (those previously mentioned). The hypotheses were tested
using structural equation modelling in the statistical tool EQS.
A questionnaire was developed that included three different parts: learning orientation, firm
innovativeness and financial performance. Questions were also included that asked about job
title, average annual sales in the business for the previous three years, the date when the firm was
established, the number of employees in the company’s production division and which products
they produced. Although all of the questions were from previous studies, the questionnaire was
tested by several researchers. Furthermore, the questionnaire was thoroughly scrutinised by a
vice-president from a firm in a corresponding industry. Because all of the questions were derived
from earlier studies, a full pilot study was not conducted.
3.3 Measurement
All latent variables were tested and measured using multiple items based on previous studies (as
recommended in’ Churchill Jr., 1979). Firm innovativeness was measured as a second-order
construct via three first-order indicators: product innovation, process innovation and business
system innovation. The firm innovativeness scale was based on previous studies (i.e., Avlonitis,
1994; Deshpandé et al., 1993; Knowles et al., 2008; Wang and Ahmed, 2004) as shown in
Appendix 1. A seven-point Likert scale was used to measure the first-order indicators, which
ranged from 1 (strongly disagree) to 7 (strongly agree).
Learning orientation was measured as a second-order construct and was measured through four
first-order indicators based on work by Calantone et al. (2002) and several earlier studies (Galer
and Van der Heijden, 1992; Hult and Ferrell, 1997; Sinkula et al., 1997). The four following
under-dimensions were commitment to learning, shared vision, open-mindedness and intraorganisational knowledge sharing. Each of the dimensions was measured using three items. The
three items with higher standard loadings based on Calantone et al.’s (2002) study were selected
(see Appendix 2). A seven-point Likert scale was used to measure the first-order indicators; the
scale ranged from 1 (strongly disagree) to 7 (strongly agree).
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Financial performance was measured using four items based on Dess and Robinson (1984).
These items were return on sales, sales growth rates, after-tax returns on assets and overall
competitiveness (see Appendix 3). The items were measured using a self-rated subjective scale,
with the respondents asked to rank their firm’s level of facility as compared with that of their
competitors in the industry. The lowest and highest quintiles were 1 and 5 respectively.
3.4 Sampling, data collection and non-response bias
Although this is a relatively large industry in the Norwegian context, there are a limited number
of firms in the industry. Through the relevant special interest organisations, we obtained contact
information for approximately 80 to 90% of the total population of firms. The data collection
process was accomplished with the help of an electronic web survey. Because there was no
access to the membership lists for the furniture industry (including via e-mail), two different
collection methods were used. Both collection methods were modified versions of the data
collection design suggested by Dilman (2000). CEOs in single-manufacturing wood-product
facilities were used as key informants because they are well positioned to evaluate different
aspects of their respective firms (Baer and Frese, 2003; García-Morales et al., 2007).
A letter was sent out to the CEOs of the furniture industry (about 100 firms) requesting that they
participate in the study. There were 36 answers received. Four hundred twenty one e-mails, each
with a link to the web study, were sent out to the CEOs in the remaining sample. After the e-mail
study was complete (in approximately four weeks), a list was made of those who had not replied
to either the postal or the e-mail inquiries. Each of the firms on this list was sent a new
questionnaire with a return envelope.
In total, there were 255 replies to 492 requests (the total made to the correct addresses). The total
response rate was therefore 52%. Of the replies received, 241 were usable. The others were
discarded because the firm had less than two employees, because it was a cooperative, because
the main office had responded instead of the production plant or division, or because the form
was not completely filled out. This procedure lowered the response rate to 49%.
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Despite a relatively high response rate, non-response bias was analysed using a t-test in which the
early and late respondents were compared (Armstrong and Overton, 1977). The firms were
compared with respect to age, size, learning orientation, firm innovativeness and financial
performance, and non-significant differences were identified (P>0.05). No non-response bias was
found (Armstrong and Overton, 1977).
4 Analyses and results
4.1.1 The measurement Model
The measurement model consisted of two second-order constructs (learning orientation and firm
innovativeness) and one first-order construct (financial performance). Firm innovativeness
consisted of three first-order factors (process, product and business systems), whereas learning
orientation consisted of four first-order factors (commitment to learning, shared vision, openmindedness and intra-organisational knowledge sharing). Each of the constructs was measured
using three to five items (Tables A1, A2 and A3 in the appendix). After testing (i.e., after
Lagrange & Wald tests and a reliability analysis had been conducted), two of the indicators for
product innovativeness were deleted because of poor metrics. Consistent with the literature, it
was considered acceptable for two error terms (“return on sales” and “return on assets”) for
financial performance to be correlated (Hansen et al., 2006). Closeness among the items may
result in repeatable errors (Gerbing and Anderson, 1984).
First-order factors
The revised measurement model with the loading coefficients and error variance for all manifest
indicators was tested. The t-values for the factor loadings varied from 10.0 to 17.5 (p < 0.01),
indicating the convergent validity of the indicators (Anderson and Gerbing, 1988). Furthermore,
reliability and variance extracted were appropriate, especially given the rather conservative
nature of the test for the latter (Hatcher, 1994). Robust estimators were used to adjust for
deviations from analysis assumptions. The measurement model showed acceptable fit (* SatorraDentler χ2 (SB χ2) = 853, df = 396, p < 0.01, * Comparative Fit Index (CFI) = 0.92, *Incremental
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Fit Index (IFI) = 0.92, * Non-normed Fit Index (NNFI) = 0.92, SBX2/df = 2.2, Standardised Root
Mean Residual (SRMR) = 0.064, * Root Mean Square Error of Approximation (RMSEA) =
0.057 [0.050, 0.064], Bollen's Rho=0.96) with 88% of the residuals in the -0.1 to +0.1 range. The
construct correlations for the first-order factors are shown in Table 1.
Table 1. Construct correlations
Second-Order
First-Order
F1 F2 F3
F1 Financial performance
1
Firm
F2 Product innovativeness
.33 1
Innovativeness F3 Process innovativeness
.47 .76 1
F4 Business System
.35 .65 .67
innovativeness
Learning
F5 Commitment to learning
.21 .43 .42
Orientation
F6 Shared vision
.24 .33 .30
F7 Open-mindedness
.28 .46 .49
F8 Intra-organisational
.11 .35 .33
knowledge sharing
Note: all significant at P<.05, except the correlation between F1and F8.
F4
F5
F6
F7
F8
1
.71
.73
.61
1
.77
.55
1
.76
1
1
.41
.33
.48
.45
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Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Second-order factors
Both the theory and the original measurement model analysis (i.e., the multicollinearity analysis)
suggested the need to assess the higher-order constructs in the model. Using Rindskopf and
Rose’s (1988) approach, higher-order constructs were sequentially added by imposing restrictions
on the less restricted model (first-order model). Using a higher-order structure indicated that the
covariation among the first-order constructs was a function of the second-order factor (Byrne,
2006). The results derived using the higher-order measurement model are presented in Figure 2
and show acceptable fit. CFI, IFI and NNFI values above 0.90 and RMSEA values below 0.06
and below 0.08 indicate that the model fit the data well. The results also show that the RMSEA,
CFI and IFI values increased when the constraints were added, which again indicates that the
model should be treated as a second-order model. All factor loadings were significant (P<0.05)
indicating the convergent validity of the indicators (Anderson and Gerbing, 1988). The
coefficient Rho is the best indicator of overall reliability given the use of correlated errors
(Bentler, 2006). The Rho value of 0.96 in this model indicates high reliability.
16
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
CR=Composite Reliability; VE= Average Variance Extracted
*SBX2 =681, df =377, p=0.00, *CFI = 0.93, *IFI = 0.93, *NNFI = 0.91, SBX2/df = 1.8, SRMR = 0.059, *RMSEA =
0.058 [0.051, 0.065], Bollen's Rho=0.96) with 91% of the residuals in the -0.1 to +0.1 range.
Figure 2 Parameters from the measurement model.
The correlations among learning orientation, firm innovativeness and financial performance are
presented in Table 2 together with the corresponding figures for discriminant validity, the items’
observed means and their standard deviations. The average variance extracted (AVE) showed that
three of the first-order constructs were below the recommended level (0.5) suggested by Fornell
and Larcker (1981). However, this is a conservative test, and all higher-order constructs were
above the suggested minimum level. Discriminant validity was tested by comparing the square
root of the AVE for a particular higher-order construct to its correlation with the other higher-
17
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
order construct, as recommended by Fornell and Larcker (1981). The results of this test provide
evidence of discriminant validity for learning orientation, firm innovativeness and financial
performance.
Table 2. Descriptives and correlation matrix for the higher-order constructs and financial
performance
Correlation
DV
Studied scales
Mean1
S.D. 1
LO
FI
LO
FI
Learning orientation (LO)
4.36
1.32
1

Firm innovativeness (FI)
4.15
1.53
.58
1


Financial performance (FP)
3.36
0.96
.27
.46
All items (except for the FP items) were measured on a 7-point interval scale ranging from 1 (strongly disagree) to
7 (strongly agree). All FP items were measured using a 5-point interval scale ranging from 1 (the lowest 20 %) to 5
(the highest 20 %)
1
Item statistics (mean of the observed items); DV () =Discriminant validity
4.1.2 Structural model
The model showed acceptable fit, with residuals that were normally distributed, small and centred
around zero (Table 3). Because of the satisfactory fit of the model, the hypotheses were evaluated
by examining the robust estimated structural path coefficients.
18
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Table 3. Results derived from the structural equation model
Model Fit
SBχ2
d.f.
*CFI
*NNFI
SRMR
*RMSEA
692
396 p>0.05
.93
.92
.061
.056 [.049,.062]
Structural model
Learning orientation -> Financial performance (FP)
Learning orientation (LO)-> Firm innovativeness (FI)
Firm innovativeness -> Financial performance
Indirect effect (LO -> FI -> FP)
R2 Firm innovativeness
R2 Financial performance
1)
Robust parameters
** = P<0.01, * = P<0.05
N.S.
.574**
.53**
.31**
.33
.28
The findings presented in Table 3 suggest that learning orientation was not directly related to
financial performance (H1: p > 0.05) during the period under study; however, the indirect effect
via firm innovativeness was significant (H4: P < 0.01). Here, learning orientation has a positive
effect on firm innovativeness (H2: p<0.01). Similarly, firm innovativeness has a positive effect on
financial performance (H3: p<0.01).
Learning orientation was hypothesised to have a positive indirect effect on financial performance
via firm innovativeness (H4). The bootstrapping method advocated by Shrout and Bolger (2002)
was used to create 1,000 bootstrap (or pseudo) samples of size 230. Subsequently, the empirical
indirect effect means and standard errors for the indirect effects were estimated. The results
indicate that the indirect effect of learning orientation on financial performance via firm
innovativeness was significant in this period (b=.218 (99% CI: .096; .339), ß=.57 x .53 = .31)
because zero is not included in the 99% confidence interval. The fact that the direct effect of
learning orientation on financial performance is not significant indicates that firm innovativeness
is acting as a full mediator.
19
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
To test for the moderating effects of firm age on the relationship between firm innovativeness and
learning orientation (H5), the dataset was first divided into ‘young firms’ and ‘old firms’(with
the groups as close to one another in size as possible). First, the parameter for learning
orientation and firm innovativeness was made equal for the two groups. In the second step, the
parameter was not restricted (Sauer and Dick, 1993). The chi-square test revealed a nonsignificant difference between the groups for the relationship between learning orientation and
firm innovativeness and failed to provide support for the existence of a moderating effect (Table
8). This suggests that age does not affect the relationship between learning orientation and firm
innovativeness (H5: p>0.05).
Because testing the direct effect of learning orientation on financial performance (H3) produced
insignificant results, the moderating effect of age on the relationship between these constructs
(H6) was not tested (Table 4). However, the model controlled for the potential moderating effects
of firm size (with the firms in the dataset divided into two groups based on their size) and
industry (with the firms in the dataset divided into primary and secondary processing firms within
the wood industry) on the relationships between learning orientation and firm innovativeness and
between firm innovativeness and financial performance. No significant difference between the
groups was found (P>0.05). Furthermore, firm size was tested as a control variable for both
dependent variables. It had a significant positive effect (p<0.05) in both cases. However, the
variable did not change the significance level of the hypotheses in the model. For the sake of
brevity, this variable was not included in the final model.
Table 4 Moderating effect of firm age on the relationships of learning orientation to firm innovativeness and
financial performance
Path
Learning orientation -> firm innovativeness
Learning orientation -> financial performance
Moderator
Firm Age
Firm Age
(P-value)
.63 (n.s.)
not tested
20
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
5 Discussion
Of the six hypotheses, three were supported. It was hypothesised when the model was
constructed that learning orientation would have a positive impact on firm innovativeness and
financial performance, with firm innovativeness acting as a mediating variable in the relationship
between learning orientation and financial performance. There was no evidence of a direct
impact of learning orientation on financial performance (H1; P > .05). These results were
surprising and inconsistent with those of Baker and Sinkula (1999), Calantone et al. (2002) and
Garcia-Morales et al. (2007). One reason for these results may be the context. For instance, in a
traditional, relatively low-technology manufacturing industry, the products, process and business
system are incorporated with one another, and therefore learning must influence financial
performance if it is also to influence firm innovativeness. Nevertheless, these findings differ from
those presented in Calantone et al.’s (2002) study. They show that firm innovativeness not only is
an important driver of financial performance but is also an important mediator of the relationship
between learning orientation and financial performance. Furthermore, these findings indicate
that the direct effects of learning orientation on firm innovativeness can be dependent on the
context of the study.
Based on these data, learning orientation is positively related to firm innovativeness (H2; β =.57,
P < .01). These findings are consistent with earlier findings (Calantone et al., 2002; Hult et al.,
2004; Rhee et al., 2009; Sinkula, 1994) and indicate the importance of a learning orientation for
firm innovativeness. Furthermore, it was suggested that firm innovativeness would have a positive
impact on financial performance, and that hypothesis was supported (H3; β =.53, P < .01). An
innovative firm is likely to have a competitive advantage and to perform better, as emphasised as
early as in Schumpeter’s work (1934). These findings are also consistent with the previous
literature (e.g. Calantone et al., 2002; Damanpour et al., 1989; Deshpandé and Farley, 2004;
Narver and Slater, 1990; Rhee et al., 2009). Nevertheless, being innovative may be costly for
firms. In particular, product and process innovation may require significant investments. Hence,
in many cases, companies will experience a time delay between the innovation and the benefits it
creates. Furthermore, being innovative involves risk, and there is no guarantee of success. For
example, Jenssen (2003) found that it is often the adopter and not the firm that creates the
innovation that receives the benefits. Nevertheless, the relationship between firm innovativeness
21
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
and financial performance was significant and positive, and this shows that companies in the
traditional wood industry in Norway can also gain from being innovative.
The moderating effect of firm age on the relationship between learning orientation and firm
innovativeness is not indicated in this study (P>.05). The findings suggest that the effect of
learning origination on firm innovativeness is constant regardless of firm age. These results are
not consistent with those attained by Calantone et al. (2002); however, their study was conducted
in a different context from the one used in the present study. The literature has emphasised the
importance to innovation of the firm’s phase in the life cycle, and a mature, traditional
manufacturing industry is likely to have more firms in later phases. Even though the previous
literature (e.g., Calantone et al., 2002 and Sikula, 1994) found age to have a moderating effect,
the results may have been compromised by simultaneous causality bias. In other words, firms that
initially develop a culture of learning orientation that ultimately facilitates firm innovativeness
and financial performance, respectively, may survive longer than firms that do not stress learning
orientation. This may explain the contradictory findings. Furthermore, it could be argued that
younger companies are not locked into ”stale” relationships and are therefore able to access more
dynamic networks. In any case, the findings presented in the present study do not indicate that
older firms are more likely than younger firms to employ knowledge and to turn it into
innovation activities.
Rhee et al. (2009) also controlled for the influence of age on the relationship between learning
orientation and firm innovativeness, and obtained the same results as this study: age did not exert
a statistically significant positive impact on firm innovativeness. Rhee et al. (2002) observed
small and medium-sized technology-intensive and innovation-oriented companies; hence, their
study was more similar to that of Calantone et al. (2002) than to this study. The article by
Calantone et al. (2002) does not mention the size of the companies they studied. It is possible that
firm size may be an important factor in the moderating effect of age; that is, a three-way
interaction effect may be at work.
22
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Given the non-significant direct relationship between learning orientation and financial
performance (H6), the moderating effect of age on these two constructs is not relevant.
Therefore, it was not tested and will not be discussed further.
6 Implications
The results of this study indicate that learning orientation is important to firm innovativeness and
financial performance. Implementing a learning orientation will help a company to increase its
firm innovativeness and improve financial performance. This study offers valuable advice and
important insights for managers seeking to create learning organisations. The findings should
make managers aware of the value of their employees and all of the knowledge that is inherent to
their organisations. A systemised process is needed for disseminating this knowledge throughout
every organisation in an efficient and effective way. These findings can help managers in
traditional manufacturing firms to change or create strategies, procedures and policies that will, in
turn, help them to create or improve important dimensions of learning orientation. These changes
do not require large investments and are therefore of help to companies at all financial levels.
The results suggest that manufacturing firms from more traditional industries must learn how to
use their commitment to learning, shared vision, open-mindedness and intra-organisational
knowledge sharing throughout the company to acquire, disseminate, share and store information
in the best and most efficient way. This study is conducted in the context of wood industry;
however, the results should likely be of equal importance for other traditional manufacturing
industries (e.g., the food, fish-farming, textile, packaging and machinery industries). In addition,
managers in traditional manufacturing industries should prioritise learning and see it as valuable
to their firms’ long-lasting competitive advantages. For this to occur, learning needs to be
emphasised and its importance acknowledged by the top management. The entire firm needs to
espouse a common focus on learning, and the employees in the different departments must have a
shared vision. Furthermore, firms and their employees must be open-minded, use critical
evaluation in a constructive way and always question assumptions. Finally, managers need to
implement a systematic approach to knowledge sharing across all units of their firms.
23
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
The even more interesting findings for managers concern the fact that learning orientation only
affects financial performance with firm innovativeness as a mediator. In other words, traditional
manufacturing firms such as those in the wood industry will not likely benefit financially from a
learning orientation without also achieving high levels of firm innovativeness. Of course, it is
important to recall the broad definition used for firm innovativeness, which includes both the
adoption and the creation of products, processes and business systems. The same result was
found for age as a moderating factor in the firm innovativeness-financial performance
relationship. The results show that in traditional manufacturing firms, the latter relationship is just
as important for young organisations as for older organisations that have had more time to
emphasise learning.
For some time, it has been argued in the literature that a learning orientation can have a direct
effect on firm financial performance (Calantone et al., 2002; Fiol and Lyles, 1985; Garvin, 1993;
Hurley and Hult, 1998; Lloréns Montes et al., 2005). Other researchers have found both direct
and indirect effects via innovation (García-Morales et al., 2007). This study, undertaken in a
traditional manufacturing context using a higher-order construct model and SEM, found only an
indirect affect. These results show that it is not a given that learning orientation will have both a
direct effect on financial performance and an indirect effect via firm innovativeness. As
previously discussed, several studies of the relationships between learning orientation, firm
innovativeness and financial performance have not created hypotheses regarding (or even
mentioned) the possibility of a direct effect of this nature. Based on the findings in the present
study, it seems possible that this is because non-significant results were obtained; however, it is
impossible to know at this time. This issue should be further investigated in another empirical
setting.
The findings also indicate the validity of Calantone et al.’s (2002) measurement model for
learning orientation. Learning orientation is a higher-order construct comprised of the factors
commitment to learning, shared vision, open-mindedness and intra-organisational knowledge
sharing. Parts of the construct have been previously tested by several researchers (e.g., Sinkula et
al., 1997) who have also found it to be valid. The findings indicate that Knowles et al.’s (2008)
measurement scale for firm innovativeness is valid as a second-order construct. Firm
24
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
innovativeness is a higher-order construct consisting of the factors product innovation, process
innovation and business system innovation. Previous researchers (Crespell and Hansen, 2008;
Knowles et al., 2008) have used the same items to calculate composite variables and have also
used them as first-order constructs in structural models. The findings derived from this study are
consistent with the scale developed by Knowles et al. (2008) and demonstrate that product
innovativeness, process innovativeness and business system innovativeness can indeed also be
used as latent variables. Hence, this study helps to develop a new measure of firm innovativeness.
7 Limitations
Like all studies, this research has limitations. It is a cross-sectional study examining a specific
point in time. Without longitudinal data, conclusions regarding causality cannot be drawn.
However, this study is well-positioned in the literature. The firms that had gone out of business
were not included in the sample, and the findings presented in this article can only be generalised
for surviving firms. This is an important limitation, especially because firm innovativeness and
financial performance are key issues here, and scholars differ in their opinions regarding how
these two factors affect firms over time.
Only subjective measures were used to assess financial performance. Although this is a common
way to measure financial performance, and although previous studies have shown strong links
between subjective and objective measures of financial performance (e.g. Dess and Robinson Jr,
1984), this aspect of the study is still considered to be one of its weaknesses. Several studies have
combined subjective and objective measures (e.g. Aragón-Correa et al., 2005), others have only
used objective measures (e.g. Jenssen, 2003). Although most researchers find a link between
innovation and financial performance when firms perceive themselves as successful, Jenssen
(2003) did not find evidence of this link when using objective measures. A study similar to the
present one using an objective measure of financial performance might lend more credibility to
the conclusions drawn here regarding the relationships between learning orientation, firm
innovativeness and financial performance.
25
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
8 Appendix
Table A1: Items used to measure firm innovativeness and the sources from which each item was
adapted.
Construct / Item
Items previously used by or
based on items from
Product Innovativeness
Our company tends to be an early adopter of new products.
(Avlonitis et al., 1994;
Deshpandé et al., 1993; Wang
and Ahmed, 2004),
Our company actively develops new products in-house.
(Avlonitis et al., 1994; Gebert
et al., 2003; Knowles et al.,
2008)
Our company actively seeks new products from outside this (Hurley and Hult, 1998; Jerezorganisation.
Gomez et al., 2005)
Our company sees creating new products as critical to our
(Avlonitis et al., 1994; Gebert
success.
et al., 2003; Knowles et al.,
2008),
Within our company, we are able to implement new
(Jerez-Gomez et al., 2005)
products used by other organisations.
When it comes to creating new products, our company is far (Gebert et al., 2003; Knowles
better than the competition.
et al., 2008)
Process Innovativeness
Our company actively develops in-house solutions to
improve our manufacturing processes.
Our company tends to be an early adopter of new
manufacturing processes.
When it comes to creating new manufacturing processes,
our company is far better than the competition.
Our company perceives creating new manufacturing
processes as critical to our success.
Business System Innovativeness
Our company actively seeks new business systems from
outside this organisation.
Within our company, we are able to implement new
business systems used by other organisations.
Our company tends to be an early adopter of new business
systems.
Our company perceives creating new business systems as
(Avlonitis et al., 1994;
Knowles et al., 2008; Vazquez
et al., 2001)
(Avlonitis et al., 1994;
Deshpandé et al., 1993; Wang
and Ahmed, 2004)
(Gebert et al., 2003; Knowles
et al., 2008; Wang and
Ahmed, 2004)
(Avlonitis et al., 1994;
Deshpandé et al., 1993;
Gebert et al., 2003; Knowles
et al., 2008)
(Hurley and Hult, 1998; JerezGomez et al., 2005)
(Jerez-Gomez et al., 2005)
(Deshpandé et al., 1993;
Wang and Ahmed, 2004)
(Gebert et al., 2003; Knowles
26
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
critical to our success.
Our company actively develops in-house business system
solutions.
et al., 2008; Wang and
Ahmed, 2004),
(Vazquez et al., 2001)
27
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Table A2. Items used to measure learning orientation and the sources from which each item was
adapted.
Construct/Item
Scale based on the work by
Commitment to learning
Managers basically agree that our organisation’s
(Calantone et al., 2002; Galer and
ability to learn is the key to our competitive advantage. Van der Heijden, 1992; Sinkula et
al., 1997)
The sense around here is that employee learning is an
(Calantone et al., 2003; Galer and
investment, not an expense.
Van der Heijden, 1992; Sinkula et
al., 1997)
Learning in our organisation is perceived as a key
(Calantone et al., 2003; Galer and
commodity necessary to guarantee organisational
Van der Heijden, 1992; Sinkula et
survival.
al., 1997)
Shared vision
There is a commonality of purpose in my organisation. (Calantone et al., 2003; Sinkula et
al., 1997)
There is total agreement regarding our organisational
(Calantone et al., 2003; Sinkula et
vision across all levels, functions and divisions.
al., 1997)
Employees view themselves as partners in charting the (Calantone et al., 2003; Sinkula et
direction of the organisation.
al., 1997)
Open-mindedness
We are not afraid to reflect critically on the shared
assumptions we have made about our customers.
Personnel in this enterprise realise that they must
continually question the very way they perceive the
marketplace.
We rarely collectively question our own bias about the
way we interpret customer information.
Intra-organisational knowledge sharing
(Calantone et al., 2002)
We always analyse unsuccessful organisational
endeavours and widely communicate lessons learned.
We have specific mechanisms for sharing lessons
learned in organisational activities from department to
department (unit to unit, team to team).
Top management repeatedly emphasises the
importance of knowledge sharing in our company.
(Calantone et al., 2002; Hult and
Ferrell, 1997)
(Calantone et al., 2002; Hult and
Ferrell, 1997)
(Hult and Ferrell, 1997a,
(Calantone et al., 2002)
(Calantone et al., 2002; Hult and
Ferrell, 1997)
(Calantone et al., 2002; Hult and
Ferrell, 1997)
28
Nybakk, E. 2012. Learning orientation, innovativeness and financial performance in traditional manufacturing firms:
a higher-order structural equation model. International Journal of Innovation Management 16(5): 28 pp.
Table A3. Items used to measure financial performance and the sources from which each item
was adapted.
Construct/Item
Return on sales (ROS)
Sales growth rate
After-tax return on assets (ROA)
Overall competitiveness
Scale based on the work by
(Dess and Robinson Jr, 1984), Hansen et al.
(2006)
(Dess and Robinson Jr, 1984), Hansen et al.
(2006)
(Dess and Robinson Jr, 1984; Lawrence and
Lorsch, 1967), Hansen et al. (2006)
(Dess and Robinson Jr, 1984)
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