Analyzing the Relationship Between KM, Innovation, and Performance

This report, based on research published in the Journal of High Technology Management Research, investigates the quantitative relationship between knowledge management (KM), innovation, and organizational performance. The study, using data from 120 Iranian firms, explores how KM activities influence innovation and firm performance, both directly and indirectly. The research model, tested using the Structural Equation Model (SEM) by Partial Least Square (PLS) method, reveals that knowledge creation, integration, and application significantly facilitate innovation and performance. Specifically, knowledge creation impacts innovation speed, quality, and quantity, while innovation quality, knowledge creation, and integration affect overall performance. The findings provide valuable insights for academics and managers in designing KM programs to enhance innovation, efficiency, and profitability. The study also reviews existing literature on KM, organizational innovation, and the dimensions of knowledge, including production, integration, and application, to provide a comprehensive understanding of the topic.

Contents lists available at ScienceDirect
Journal of High Technology Management Research
journal homepage: www.elsevier.com/locate/hitech
The Relationship Between Knowledge Management and Innovation
Performance
Amirhosein Mardania,⁎, Saghi Nikoosokhanb, Mahmoud Moradib,
Mohammad Doustarb
aFaculty of Management, University of Tehran, Jalal-al-Ahmed, Tehran, Iran
b Department of Management, University of Guilan, Rasht-Tehran Road, Rasht, Iran
A R T I C L E I N F O
Keywords:
Knowledge Management
Knowledge Creation
Knowledge Integration
Innovation Performance
A B S T R A C T
This study examines the quantitative relationship between knowledge management, innovation
and performance.We aim to shed some light on the consequences of Knowledge Management
(KM) activities on firm's innovation and performance.Organizations are unaware ofreal im-
plications of KM.According to the literature review,we develop a research modelshowing a
positive relationship between knowledge management, and performance as well as its impact o
innovation, which in turn contributes to the firm's performance. Using data from 120 firms that
are members of the Iranian Power Syndicate,this modelwas tested empirically.Based on the
StructuralEquation Model(SEM) results by PartialLeastSquare (PLS) method,research hy-
potheses were supported. Results show that KM activities impact innovation and organizational
performance directly, and indirectly through an increase in innovation capability. It is found tha
knowledge creation, knowledge integration, and knowledge application facilitate innovation and
performance.Knowledge creation has more significant effects on innovation speed,innovation
quality,and innovation quantity,whereas innovation quality,knowledge creation,and knowl-
edge integration has more significant effects on performance.Findings presented in this paper
may help academics and managers in designing KM programs to achieve higher innovation,
effectiveness, efficiency, and profitability.
1. Introduction
“The modern corporation,as it acceptsthe challengesof the new knowledge-based economy,will need to evolve into a
knowledge-generating,knowledge-integrating and knowledge protecting organization” (Teece,2000,p. 42). Hence,firms have to
continuously work on their specific capabilities,(e.g.dynamic capabilities) to stay competitive.(Teece & Pisano,1994).Skyrme
(2001) defines Knowledge Management (KM) as ‘the explicit and systematic management of vitalknowledge,and its associated
processes of creation,organizing,diffusion,and exploitation’.From the practice perspective,firms are noticing the importance of
managing knowledge if they want to remain competitive (Zack, 1999), and grow (Salojärvi, Furu, & Sveiby, 2005).
In the era of knowledge-based economy, resources and competencies are expected to be the crucial factors for organization
survive in dynamic and competitive environment (Subramaniam & Youndt, 2005; Teece, Pisano, & Shuen, 1997). After pointing
that knowledge is an alternative to equipment, capital, materials, and labor to become the most important element in productio
Drucker (1993) predicted thatcompetitive advantage in future isdetermined by knowledge resources,or what is known as
https://doi.org/10.1016/j.hitech.2018.04.002
⁎ Corresponding author.
E-mail address: [e-mail] (A. Mardani).
Journal of High Technology Management Research 29 (2018) 12–26
1047-8310/ © 2018 Elsevier Inc. All rights reserved.
T

knowledge workers.
In the dynamic capabilities approach that roots in the resource-based view of the firm by Penrose (1959),a pivotal role for
strategic management is opened (Kor & Mahoney, 2004). Among the management objectives proposed by this approach, the m
agement of a firm's knowledge resources, with respect to a firm's innovativeness, has increasingly attracted attention over the
decade. An increasing amount of research on innovation and strategic management puts knowledge in the center of interest (D
2005; Davenport, De Long, & Beers, 1997; Grant, 1996; Hall & Andriani, 2002; Hargadon, 1998; Nonaka & Takeuchi, 1995; Swa
Newell, Scarbrough, & Hislop, 1999). In the innovation literature, knowledge is discussed as the element of a recombination pro
to generate innovation (Galunic & Rodan, 1998; Grant, 1996). Knowledge has an inherent value to be managed, applied, develo
and exploited. Knowledge can be seen as an asset that raises traditional asset questions to management such as when, how m
what to invest in. As the necessary intangible assets for any organizations, knowledge should be elaborately managed. Conseq
both scholars and practitioners have increasingly paid great attention to an organization's ability to identify, capture, create, sh
accumulate knowledge (Jang, Hong, Bock, & Kim, 2002; Kogut & Zander, 1996; Michailova & Husted, 2003; Nonaka & Takeuchi,
1995).Owing to the particular properties of knowledge,however,knowledge assets require special attention.Knowledge is often
embedded in employees, has features of a public good (Jaffe, 1986, p. 984; Liebeskind, 1997), and can hardly be bought in the
(Hall and Mairesse, 2006, p. 296). Therefore, innovating firms need a sophisticated Knowledge Management (KM) that pays a lo
attention to the special requirements of interactive knowledge, and dimensions of knowledge (creation). Particularly in the eme
distributed organizations,effectiveness is highly dependent on how well knowledge is shared between individuals,teams,and/or
units (Alavi & Leidner, 2001; Argote & Ingram, 2000; Huseman & Goodman, 1998;Pentland, 1995). Knowledge sharing behavior
have been argued to contribute to the generation of various organizational capabilities such as innovation, which is vital to a fir
performance (Kogut & Zander, 1996). The importance of KM and its relationship with innovation is widely acknowledged. Howev
it is difficult to draw conclusions from the extant literature about the relationship between effective KM,innovation,and perfor-
mance.Empiricalwork, however,is still in its infancy,and characterized by heterogeneous measurement approaches (Halland
Mairesse, 2006, p. 296). Various studies on technological (ICT-based) (Adamides & Karacapilidis, 2006), human resource (Carte
Scarbrough, 2001), or social aspects (Gupta & Govindarajan, 2000) of KM exist, focusing on innovation types in general (Darroc
2005). Despite the importance of these results, approaches that attempt to measure firms'success with innovations achieved through
KM when innovation success is quantified (measured in economic terms such as sales generated) are still scarce. The first step
this gap in the literature is presented in this paper.
This study aims to examine the relationships between knowledge management activities, innovation, and firm performance
a holistic perspective. According to a survey including 226 experts from 120 enterprises in Iran, which are the members of Irani
power syndicate, this study employed modeling to investigate the research hypotheses within their organizations.
Thus, the following questions may arise: whether Knowledge creation, knowledge integration, knowledge application influen
firm performance directly? What are the key factors affected by knowledge management activities that lead to firm performanc
Does KM, through innovation, have an impact on a firm's success? According to knowledge management literatures, this paper
that Knowledge creation,knowledge integration,and knowledge application not only have positive relationship with firm perfor-
mance directly but also influence innovation speed, quality and quantity that are related to firm performance.
The remainder of this paper proceeds as follow:Section 2 presents the literature review for introducing key constructs of our
research. Section 3 develops a research model to depict hypothesized relationships.Section 4 provides research methodology and
data collection. Data analysis and the findings are reported in Section 5. Finally, conclusions, limitations and further research su
gestions are presented in Section 6.
2. Literature Review
Our literature review is centered on our main research question: “Does KM have impacts on a firm's success through innova
Before reviewing studies dealing with the link between KM and the success of innovation activities, we start our literature revie
with papers related to definitions and forms of KM.
2.1. Knowledge Management
Gold, Malhortra,and Segars (2001) examined the issue of effective Knowledge Management (KM) from the perspective of or-
ganizational capabilities. This perspective states that a knowledge infrastructure including technology, structure, and culture al
with a knowledge process architecture ofacquisition,conversion,application,and protection are essentialorganizationalcap-
abilities,or “preconditions” for effective knowledge management.The results provide a basis to understand the competitive pre-
disposition of a firm as it enters a program of KM. Cui, Griffith, and Cavusgil (2005) also mentioned that KM capabilities consist
three interrelated processes: knowledge acquisition, knowledge conversion, and knowledge application (Gold et al., 2001). Kno
edge is not only an important resource of a firm, but it also is a main source of competitive advantage (Gold et al., 2001; Grant,
Jaworski & Kohli, 1993). Therefore, KM capabilities refer to the knowledge management processes that develop, and use knowle
within a firm (Gold et al., 2001).
Several definitions have been around KM (Alavi & Leidner, 2001; Coombs & Hull, 1998; Davenport & Prusak, 1998; Nonaka &
Takeuchi, 1995; Probst, Raub, & Romhardt, 1999). Different approaches to KM concentrate on the creation, diffusion, storage, a
application of existing, or new knowledge (e.g. Coombs & Hull, 1998). Wiig (1997) puts his emphasis on the management of ex
knowledge, Wiig states that the purpose of KM is “to maximize the enterprise's knowledge related effectiveness and returns fro
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
13

knowledge assets, and to renew them constantly” (Wiig, 1997, p. 2). Davenport and Prusak (1998) stress that KM consists of m
knowledge visible and developing a knowledge-intensive culture. Several studies identified acquisition, identification, developm
diffusion, usage, and repository of knowledge as core KM processes (e.g. Alavi & Leidner, 2001; Probst et al., 1999). Swan, New
Scarbrough, et al. (1999) argue that knowledge exploration and exploitation are the core objectives of KM. KM implementation
be divided into IT-based KM, and human-resource-related KM, as well as process-based approaches (Tidd, Bessant, & Pavitt, 20
IT-based or supply-driven KM emphasizes the need for (easy) access to existing knowledge stored in databases,or elsewhere
(Swan, Newell, Scarbrough,et al., 1999). In contrast, the demand-driven approach is more concerned with facilitating interactive
knowledge sharing, and knowledge creation (Swan, Newell, Scarbrough, et al., 1999).
Although there are still many classifications of KM, this study prefers three Dimensions of knowledge. These dimensions are
follow:
1. Production of Knowledge including knowledge acquisition, and knowledge creation
2. Integration of Knowledge including knowledge storage, and knowledge distribution
3. Application of Knowledge including protection, and use of knowledge
2.2. OrganizationalInnovation
Basically, there are two types of innovation: product and process innovation (Dosi, 1988; Teece, 1989; Utterback & Abernath
1975).These are not mutually preclusive,but depend on each other in a major degree.Process innovations can furthermore be
divided into organization (i.e. new market organization and internal company organization), and technology (i.e. human artifact
Technology can be classified as three entities (Gehlen, 1980, p. 19): instrument, machine, and automaton. This concept of tech
separates us from Johnson (1992, p. 28), among others, where he makes the following statement: “knowledge used in the prod
process is called technology”. This question should be asked from Johnson: what about “tacit knowledge”? If “tacit knowledge”
a part of the technology concept, technology will lose its analytical purpose. This also applies if all explicit knowledge is include
the technology concept.
Innovation can also be seen as incremental(i.e. small step-by step improvements,or continuous innovation),or radical (i.e.
something qualitatively new, or a breakthrough) (Dewar & Dutton, 1986; Ettlie, Bridges, & O'Keffe, 1984; Freeman, 1992; Mans
1968; Mokyr, 1990; Zaltman, Duncan, & Holbek, 1973). Continuous and radical innovation can also be autonomous. One examp
autonomous innovation is “snowboard”.One example of systemic innovation is IBM's OS/2,which presupposed change in other
systems in the value chain.
The growth innovation literature provides many alternative conceptualizations and models for the interpretation of observed
data. An innovation can be a new product or service, a new production process technology, a new structure or administrative sy
or a new plan or program pertaining to organizational members. Therefore, organizational innovation or innovativeness is typic
measured by the rate ofinnovation adoption.A few studies,however,have used other measures to measure organizationalin-
novativeness (Damanpour, 1991). Former research has argued that different types of innovation are necessary for understandi
identifying in organizations.
Among numerous typologies of innovation in the literature, three have gained the most attention. Each centers on a pair of
of innovation: administrative and technical, product and process, and radical and incremental. Wang and Ahmed (2004) identifi
organizational innovation through an extensive literature. These five dimensions are tested from component factors. They are p
innovation, market innovation, process innovation, behavioral innovation, and strategic innovation. Although there are still man
classifications of innovation, this study prefers three aspects of innovation:
1. Innovation speed;
2. Innovation quality; and
3. Innovation quantity.
Innovation speed, which is defined as the time elapsed between initial development, including the conception and definition
innovation, and ultimate commercialization of a new product or services into the marketplace, reflects a firm's capability to acc
erate activities and tasks,build a competitive advantage relative to its competitors within industries with shortened product life
cycles (Allocca & Kessler, 2006; Kessler & Bierly III, 2002; Kessler & Chakrabarti, 1996). Emphasis on innovation speed represen
paradigm shiftfrom traditionalsources ofadvantage to a strategic orientation,specifically suited for today's rapidly changing
business environments.Innovation speed is a crucialelementto compete in the marketand can lead to superior performance.
Empirical studies confirm a positive relationship between speed-to-market and overall new product success (Carbonell & Escud
2010; Carbonell & Rodriguez, 2006; Carbonell & Rodriguez-Escudero, 2009). Since innovation speed is a team embodied and so
complex capability- that cannot be easily developed or imitable by competitors (Slater & Mohr, 2006)- it enables firms to keep i
close touch with customers, and their needs (Tatikonda & Montoya-Weiss, 2001). Furthermore, the increasing rate of competitio
technological developments in the marketplace,and shorter product life cycles force companies to hasten innovation (Heirman &
Clarysse, 2007).
The concept of innovation quality allows us to make a statement regarding the aggregated innovation performance in every
domain within an organization,by comparing the result,being a product,process or service innovation,with the potentialand
considering the process on how these results have been achieved (Haner,2002;Lanjouw & Schankerman,2004).With respect to
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
14

products or services, innovation quality may be defined through variables such as effectiveness, features, reliability, timing, cos
complexity,innovation degree,value to the customer,and more.Similar are the things with respectto the process domain of
innovation quality. Although innovation quality is one of the most important factors for the company that applies innovation stra
to compete in the market,determining it might be faced with more challenges due to the increased complexity,the difficulty to
identify catalysts,and the need to integrate measurements on so-called soft issues(e.g.relative citation ratio,citation-weighted
patents, science linkage, scope of innovations, and so on) (Lahiri, 2010; Ng, 2009; Tseng & Wu, 2007).
Quantity innovation is defined as the number of new or improved products and services launched to the market that are sup
to the average of the industry. It also is defined as the number of new or improved processes that are superior to the average o
industry.
Organizational interest in KM is stimulated by the possibility of subsequent benefits such as increased creativity, and innova
in products and services (Darroch, 2005; Moffett, McAdam, & Parkinson, 2002). In fact, knowledge contributes to producing crea
thoughts and generating innovation (Borghini,2005). That is why innovation is seen as the area ofgreatestpayoff from KM
(Majchrzak, Cooper, & Neece, 2004).
2.3. Knowledge Management and Innovative Success
Looking at the relationship between KM and innovation activities we first draw on Schumpeter. According to him, innovation
the result of a recombination of conceptual and physical materials that were previously in existence (Schumpeter, 1935). In oth
words, innovation is the combination of a firm's existing knowledge assets to create new knowledge. Therefore, the primary tas
the innovating firm is to reconfigure existing knowledge assets and resources,and to examine new knowledge (Galunic & Rodan,
1998; Grant, 1996; Nonaka & Takeuchi, 1995). Both exploration and exploitation of knowledge have been shown to contribute t
innovativeness of firms,and to its competitive advantage (Hall & Andriani,2002;Levinthal & March,1993;March, 1991;Swan,
Newell, Scarbrough, et al., 1999). Various studies focus on the role of KM in the innovation process. The results found by Liao an
Chuang (2006) support the vitalrole of KM in knowledge processing capability and in turn,in speed and activity of innovation.
Huergo (2006) provides evidence to support the positive role of technology management in success of firm innovations. A diffe
approach is applied by Yang (2005). He assumes that moderating effects of marketing and manufacturing competencies, know
acquisition, knowledge dissemination,knowledge integration,and knowledge innovation improve new product performance.This
finding is supported by Brockman and Morgan (2003).They argue thatthe KM tools such as “use ofinnovative information”,
“efficient information gathering” and “shared interpretation” improve the performance and innovativeness of new products.With
regard to specialfocus on “demand-driven”,or “collaborative” KM methods,theoreticalconsiderations provide ambiguous argu-
ments. Alavi and Leidner (2001) argue that excessively close ties in a knowledge-sharing community may limit knowledge crea
due to redundant information. On the other hand, Brown and Duguid (1991) and Nonaka, Toyama, and Konno (2000) make the
that a shared knowledge base increases knowledge creation within the community.Empiricalcase study evidence shows mixed
results as well. Findings of Darroch et al. are a good example. Darroch (2005) confirms the positive role of knowledge dissemina
on innovation success, while Darroch and McNaughton (2002) do not find any significant effects. Another aspect of the link betw
KM and innovation is how different types of innovation are affected by KM. According to Darroch and McNaughton (2002) differe
types of innovation require different resources and hence a differentiated KM strategy. They investigate the effects of KM on th
types of innovation. According to their findings different KM activities are important for different types of innovative success. He
we expect that KM acts differently on different type of innovation success, as well as speed, quality, and quantity innovation su
3. Consequences of KM and Innovation Success
3.1. Effects of KM on innovation
The innovative efforts include discovery, experimentation, and development of new technologies, new products and/or servi
new production processes,and new organizationalstructures.Innovation is about implementing ideas (Borghini,2005).The Lit-
erature (Daft, 1982; Damanpour & Evan, 1984) describes innovation as internally acquired element, new structure or administr
system,policy, new plan or program,new production process,and product,or service to a company.Innovation process highly
depends on knowledge (Gloet & Terziovski,2004),specially tacit knowledge (Leonard & Sensiper,1998). Transforming general
knowledge into specific knowledge,new and valuable knowledge is created and converted into products,services,and processes
(Choy,Yew, & Lin, 2006).Studies on knowledge creation by Nonaka consider knowledge as a main requisite for innovation and
competitiveness (Nonaka,1994).A KM system that expands the creativity envelope is thought to improve the innovation process
through quicker access and trend of new knowledge (Majchrzak et al., 2004). Also, effective KM is a critical success factor to launch
new products. In this sense, this paper supports that one of the factors influencing innovation capacity in organizations is know
and its management. Darroch (2005) provides empirical evidence to support the view that a firm with a capability in KM is also
to be more innovative. Also, Massey, Montoya-Weiss, and O'Driscoll (2002) tell the story of a real company that implemented a
strategy,and enhanced innovation process and performance.Swan,Newell, and Robertson (1999) also compared the impact on
innovation in different KM programs implemented in two organizations.
Thus,a close link between the organization's knowledge and its capacity to innovate exists (Borghini,2005).A few empirical
research has specifically addressed antecedents and consequences of the production, Integration, and Application of Knowledg
innovation,and performance.The management of knowledge is frequently identified as an important antecedent of innovation.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
15

Effective KM is presented in the literature as a method for improving innovation and performance. We obtained the result that K
processes positively affect innovation. Therefore, it is fair to conclude that KM process and innovation are closely related. Thus,
posit the followings:
H1. The production of knowledge has a direct and significant effect on speed innovation.
H2. The Integration of Knowledge has a direct and significant effect on speed innovation.
H3. The Application of Knowledge has a direct and significant effect on speed innovation.
H4. The production of knowledge has a direct and significant effect on quality innovation.
H5. The Integration of Knowledge has a direct and significant effect on quality innovation.
H6. The Application of Knowledge has a direct and significant effect on quality innovation.
H7. The production of knowledge has a direct and significant effect on quantity innovation.
H8. The Integration of Knowledge has a direct and significant effect on quantity innovation.
H9. The Application of Knowledge has a direct and significant effect on quantity innovation.
3.2. KM Effects on Organizational Performance
Prior conceptualresearch state thatKM can improve corporate performance and competitiveness (Civi,2000; DeTienne &
Jackson, 2001; Holsapple & Jones, 2004, 2005). KM programs are successful as corporate performance is improved. Therefore, i
essentialto measure KM contributions to performance (Tseng,2008),especially when there is no conclusive research on the re-
lationship between the production,Integration,Application of knowledge and firm performance (Yang,2010).Corporate perfor-
mance is a multidimensional concept and accounts for firm's position regarding to competitors. A comprehensive view of corpo
performance not only considers the financial perspective, but also others aspects that allow monitoring value creation. Based o
view some methodologies have been developed. The most popular methodology is the Balanced Scorecard (Kaplan & Norton, 1
Some studies recognize the impact of strategic KM on different dimensions of corporate performance (McKeen, Zack, & Singh, 2
Nevertheless,most of them focus on hard financialoutcomes (e.g.cost,profit, etc.) to evaluate KM (Vaccaro,Parente,& Veloso,
2010), while ignoring soft non-financial outcomes such as operating costs, shorten lead-time, and differentiate products (Sher &
2004); developing new services (Storey & Kahn, 2010); improving its ability to attract, train, develop, and retain employee (Tho
& Keithley, 2002); and improving coordination efforts (Wu & Lin, 2009). since diverse dimensions of performance are affected b
strategy, K M system performance should combine financial and nonfinancial measures (Tseng, 2008; Wu & Lin, 2009). We sug
that the impact of KM strategy on firm performance should be better studied by analyzing different dimensions of corporate pe
formance.Three dimensions will be employed to measure KM contributions to corporate performance:(1) financialperformance
including market performance (profitability, growth and customer satisfaction); (2) process performance, which refers to quality
efficiency;and (3) internalperformance,which relates to individualcapabilities (employees'qualification,satisfaction and crea-
tivity). Thus, this study proposes:
H10. The production of knowledge has a direct and significant effect on organizational performance.
H11. The Integration of Knowledge has a direct and significant effect on organizational performance.
H12. The Application of Knowledge has a direct and significant effect on organizational performance.
3.3. Innovation Effects on OrganizationalPerformance
Innovation is recognized as a significant enabler for firms to create value and sustain competitive advantage in the increasin
complex and rapidly changing environment (Bilton & Cummings, 2009; Subramaniam & Youndt, 2005). In general, innovation n
only makes full use of existing resources,improve efficiency and potential value,but also brings new intangible assets into orga-
nization.Firms with greater innovativeness willbe more successfulin responding to customers'needs,and in developing new
capabilities that allow them to achieve better performance or superior profitability (Calantone, Cavusgil, & Zhao, 2002; Sadikog
Zehir, 2010). Innovation is critical to achieve operationalefficiency aswell as raising service quality (Hsueh & Tu, 2004;
Parasuraman,2010). Accordingly,scholars paid more attention to the effects on firm performance (Clifton,Keast,Pickernell,&
Senior, 2010;Jenny, 2005; Liao, Wang, Chuang, Shih, & Liu, 2010; Vaccaro et al., 2010).
As time-based competition has become an important concern for contemporary business organizations,more firms recognized
that quick response of their competitors to new product development is posing a critical competitive threat. Therefore, they att
to introduce new products, services, or processes more quickly (Boyd & Bresser, 2008; Smith, 2011). Robinson (1990) demonst
that over a broad cross-section of industries, firms that stressed innovation speed could increase their market share. When a fir
faster than its competitors in developing, producing and selling new products, it is able to make market segments in association
service quality and operating efficiency.That is because knowledge contained in these innovations is notreadily available to
competitors (Liao et al., 2010). Therefore, innovation speed guarantees quicker response to environment by launching new pro
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
16

with lower times and costs,which eventually improves firm performance (Tidd,Bessant,& Pavitt, 2005).Innovation quality is
another key factor influencing firm performance.A high quality of innovation is adopting numerous new products,processes or
practices across a broad cross-section of organizational activities. It requires firms to create synergies among these multiple ac
domains.Such synergies should be created in a way that is inimitable,encourages newness and contributes to competitiveness.
Organizations benefit from increased ideas. Innovative R&D would be more effective in achieving firm performance goals (Bren
2001; Singh, 2008).
Quantity innovation which is defined as the number of new or improved products, services and process launched to the mar
superior to the average in your industry. In fact, knowledge contributes to producing creative thoughts and generating innovati
(Borghini,2005).That is why innovation is seen as the area of greatest payoff from KM (Majchrzak et al.,2004).Although the
relationships between innovation and firm performance have been discussed,few researches consider the specific effects ofin-
novation speed, quality, and quality on firm's performance. So this paper proposes the hypotheses as follow:
H13. Speed innovation has a direct and significant effect on organizational performance.
H14. Quality innovation has a direct and significant effect on organizational performance.
H15. Quantity innovation has a direct and significant effect on organizational performance.
4. Research methodology
4.1. Construct operationalization
To test the research model,a survey was conducted by companies that are members of Iranian Power Syndicate.A structured
questionnaire consisting of close-ended questions was developed. Pretest for the instrument was examined by 6 practitioners (
senior managers, senior experts of five companies), and 5 academics. The questionnaire was localized for Iran. The seven-point
scale ranging from “1” (totally disagree) to “7” (totally agree) was employed in the questionnaire.The question items for the
constructs are listed in Appendix A.
The variables of this research are measured using multi-item scales, tested in previous studies. The producing of knowledge
is based on Fong and Choi (2009). A range of studies (Fong & Choi, 2009) were used to determine the item scale of the knowled
integration. The Application of Knowledge is measured based on Fong and Choi (2009). Innovation speed was measured using fi
items reflecting firm quickness to generate novel ideas, new product launching, new product development, new processes, and
problem solving compared to key competitors.A few studies used similar measures to operationalizefirm's response speed to
competitive actions (Chen & Hambrick, 1995; Liao et al., 2010). The measurement of innovation quality was developed from Ha
(2002) and Lahiri (2010). Five items reflect the newness and creativity of new ideas, products, processes, practices, and manag
of certain company. Quality Innovation scale is based on Lee and Choi (2003). Finally, performance measures are based on Qui
Rohrbaugh (1983), Hoque and James (2000), and Choi and Lee (2002, 2003).
4.2. Data Collection
This study examined a sample of 120 firms that are the members of Iranian Power Syndicate.These firms varied in size and
industry.The sample has several advantages.First, production,integration,and application of Knowledge in knowledge intensive
firms plays a crucial role in facilitating innovation (e.g. designing new products or services in this highly competitive arena). Sec
today's dynamic economy depends on the developmentof innovation.This property makes firms to examine the link between
innovation and performance. Data were collected from CEO, senior manager, expert, and senior expert as the key informant du
their knowledge of the firm,access to strategic information,and familiarity with the environment.Informants were promised to
obtain a summary of the results if they were interested in this study. 226 questionnaire were collected.
5. Results
5.1. Results of reliability and validity
Using SPSS and PLS,we conducted a StructuralEquation Model(SEM) to evaluate the overallmeasurement model,and per
construct. Measurement model shows high reliability and validity of the scales (Table 1). Concerning reliability, Cronbach's alph
Eigen value and Dillon-Goldstein's Rho are above 0.7 level recommended by the literature (Hair, Anderson, Tatham, & Black, 20
To evaluate the validity of measurement model, convergent validity and discriminant validity were assessed. Convergent validi
the degree to which, factors that are supposed to measure a single construct, confirm each other. We tested convergent validit
recommended by other studies. Except the Integration of Knowledge (which was 0.42), the average variance extracted is above
the minimum value proposed by Fornelland Larcker (1981).As it is seen in Table 1,the results show that our modelmeets the
convergent validity criteria.
Discriminant validity is the degree to which, factors that are supposed to measure a specific construct do not predict concep
unrelated criteria (Kline, 2010). We used Fornell and Larcker's approach to assess discriminant validity. In this approach, the AV
per construct should be higher than the squared correlation between the construct, and any of the other constructs. Table 1 ind
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
17

that the measurement model has satisfactory discriminant validity.
5.2. The evaluation of structural model
Structural model (Table 2) supports the existence of Knowledge Management Dimensions: The production of knowledge (ite
Table 1
The results of reliability and validity basis on the scale measure the constructs in the conceptual model.
Critical ratio (CR) Standard error loadings perf i.qaun i.qau i.spe k.app k.int k.pro variables Constructs
13.191 0.048 0.634 0.452 0.324 0.448 0.285 0.529 0.529 0.634 k.pro1 Production of
knowledge15.098 0.042 0.636 0.470 0.307 0.490 0.364 0.369 0.453 0.636 k.pro2
16.331 0.043 0.699 0.500 0.228 0.401 0.414 0.471 0.592 0.699 k.pro3
11.288 0.057 0.645 0.433 0.131 0.372 0.304 0.437 0.452 0.645 k.pro4
22.280 0.035 0.788 0.546 0.297 0.490 0.378 0.510 0.557 0.788 k.pro5
21.683 0.035 0.754 0.566 0.293 0.486 0.396 0.446 0.519 0.754 k.pro6
24.054 0.031 0.752 0.523 0.240 0.474 0.376 0.516 0.530 0.752 k.pro7
29.813 0.028 0.825 0.552 0.284 0.527 0.414 0.554 0.592 0.825 k.pro8
19.931 0.039 0.768 0.545 0.390 0.562 0.437 0.533 0.589 0.768 k.pro9
16.776 0.042 0.705 0.478 0.272 0.410 0.286 0.494 0.577 0.705 k.pro10
9.830 0.064 0.626 0.428 0.180 0.361 0.276 0.516 0.626 0.562 k.int1 Integration of
Knowledge8.575 0.067 0.576 0.382 0.291 0.361 0.301 0.370 0.576 0.431 k.int2
9.246 0.066 0.610 0.321 0.239 0.279 0.201 0.498 0.610 0.357 k.int3
10.700 0.053 0.568 0.378 0.186 0.266 0.258 0.376 0.568 0.376 k.int4
9.785 0.063 0.612 0.472 0.199 0.314 0.231 0.469 0.612 0.468 k.int5
9.229 0.061 0.560 0.399 0.154 0.290 0.261 0.459 0.560 0.496 k.int6
15.855 0.046 0.737 0.531 0.281 0.506 0.486 0.564 0.737 0.639 k.int7
16.138 0.042 0.683 0.448 0.332 0.373 0.294 0.554 0.683 0.459 k.int8
10.128 0.059 0.597 0.258 0.235 0.236 0.176 0.486 0.597 0.346 k.int9
17.054 0.040 0.679 0.399 0.216 0.301 0.268 0.541 0.679 0.480 k.int10
19.649 0.038 0.742 0.508 0.301 0.426 0.381 0.614 0.742 0.576 k.int11
15.280 0.044 0.666 0.463 0.322 0.391 0.345 0.504 0.666 0.540 k.int12
22.984 0.033 0.760 0.489 0.262 0.418 0.395 0.619 0.760 0.534 k.int13
13.732 0.044 0.610 0.444 0.227 0.384 0.342 0.514 0.610 0.467 k.int14
11.794 0.060 0.709 0.307 0.158 0.231 0.231 0.709 0.543 0.397 k.App1 Application of
Knowledge12.095 0.057 0.691 0.303 0.206 0.266 0.237 0.691 0.506 0.350 k.App2
12.177 0.051 0.624 0.433 0.105 0.379 0.280 0.624 0.504 0.490 k.App3
19.352 0.040 0.774 0.375 0.268 0.331 0.330 0.774 0.639 0.451 k.App4
35.643 0.023 0.828 0.532 0.289 0.455 0.399 0.828 0.648 0.511 k.App5
12.766 0.052 0.659 0.466 0.246 0.345 0.265 0.659 0.516 0.473 k.App6
14.733 0.046 0.680 0.502 0.226 0.464 0.343 0.680 0.612 0.625 k.App7
13.081 0.052 0.675 0.455 0.275 0.480 0.385 0.675 0.485 0.581 k.App8
21.691 0.035 0.767 0.463 0.324 0.576 0.767 0.319 0.365 0.373 i.spe1 Innovation speed
33.936 0.025 0.834 0.507 0.568 0.634 0.834 0.317 0.344 0.390 i.spe2
25.202 0.032 0.798 0.422 0.453 0.572 0.798 0.283 0.321 0.331 i.spe3
22.023 0.035 0.763 0.405 0.358 0.528 0.763 0.385 0.441 0.455 i.spe4
16.407 0.043 0.713 0.464 0.253 0.556 0.713 0.390 0.389 0.429 i.spe5
16.014 0.045 0.721 0.500 0.351 0.721 0.581 0.413 0.407 0.447 I.qua1 Innovation quality
16.127 0.045 0.728 0.452 0.454 0.728 0.600 0.293 0.314 0.400 I.qua2
19.598 0.039 0.758 0.525 0.470 0.758 0.592 0.368 0.382 0.418 I.qua3
19.838 0.038 0.757 0.541 0.384 0.757 0.521 0.398 0.419 0.475 I.qua4
20.103 0.039 0.787 0.647 0.336 0.787 0.524 0.443 0.510 0.628 I.qua5
45.965 0.020 0.925 0.477 0.925 0.458 0.461 0.297 0.348 0.316 i.quan1 Innovation quantity
31.304 0.028 0.885 0.431 0.885 0.484 0.451 0.280 0.353 0.411 i.quan2
22.720 0.032 0.723 0.723 0.444 0.617 0.510 0.406 0.475 0.523 perf1 Performance
14.303 0.047 0.668 0.668 0.319 0.437 0.423 0.334 0.394 0.407 perf2
19.575 0.041 0.804 0.804 0.351 0.546 0.429 0.445 0.476 0.557 perf3
16.692 0.045 0.744 0.744 0.440 0.541 0.472 0.400 0.456 0.512 perf4
17.988 0.038 0.692 0.692 0.308 0.529 0.386 0.461 0.526 0.535 perf5
16.252 0.043 0.703 0.703 0.431 0.494 0.343 0.437 0.495 0.485 perf6
25.253 0.030 0.766 0.766 0.301 0.493 0.423 0.419 0.484 0.538 perf7
17.539 0.041 0.713 0.713 0.266 0.460 0.408 0.500 0.532 0.574 perf8
17.252 0.037 0.639 0.639 0.339 0.481 0.303 0.339 0.348 0.367 perf9
16.456 0.040 0.662 0.662 0.437 0.593 0.450 0.456 0.498 0.457 perf10
The results (AVE) are > 0.50, except the integration of
knowledge which is 0.42
0.508 0.820 0.563 0.602 0.501 0.420 0.523 Convergent validity
The results (AVE) are more than the correlation coefficients
between constructs
0.713 0.906 0.750 0.776 0.708 0.648 0.723 Discriminant validity
Results are > 0.70 0.892 0.779 0.809 0.834 0.856 0.893 0.896 Cronbach's alpha
Results are > 0.70 0.913 0.903 0.868 0.884 0.891 0.911 0.915 Dillon-Goldstein's Rho
Bold indicates high numbers of discriminant validity.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
18

Table 2
Relationships indices between latent variable and manifest variables.
Coefficient of determination and test them Independent construct Dependent construct Value Standard error Critical ratio (CR)
Variable's R2 R2 Standard error Standard error
5.327 0.052 0.279 0.107 10.516 0.020 0.208 Innovation speed Production of knowledge
0.094 10.123 0.019 0.195 Integration of Knowledge
0.078 8.053 0.022 0.178 Application of Knowledge
7.839 0.056 0.440 0.337 7.072 0.073 0.515 Innovation quality Production of knowledge
0.070 2.099 0.060 0.126 Integration of Knowledge
0.034 0.764 0.085 0.065 Application of Knowledge
3.821 0.043 0.166 0.064 7.645 0.021 0.161 Innovation quantity Production of knowledge
0.061 6.846 0.023 0.157 Integration of Knowledge
0.042 5.542 0.023 0.130 Application of Knowledge
14.902 0.043 0.640 0.132 23.158 0.008 0.187 Performance Production of knowledge
0.116 19.824 0.009 0.176 Integration of Knowledge
0.093 18.242 0.009 0.157 Application of Knowledge
0.091 13.471 0.012 0.156 Innovation speed
0.140 23.284 0.008 0.193 Innovation quantity
0.067 12.519 0.011 0.134 Innovation quality
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
19

K.pro1, K.pro2, K.pro3, K.pro4, K.pro5, K.pro6, K.pro7, K.pro8, K.pro9 and KMS10 in Appendix A), The Integration of Knowledge
(items K.int1, K.int2, K.int3,K.int4, K.int5, K.int7, k.int8, k.int9, k.int10, k.int11, k.int12, k.int13, k.int14), and The Application of
Knowledge (k.App1, k.App2, k.App3, k.App4, k.App5, k.App6, k.App7, k.App8). Second structural model also supports the existe
of three innovation variables:speed innovation (i.spe1,i.spe2,i.spe3,i.spe4,i.spe5),quantity innovation (I.qua1,I.qua2,I.qua3,
I.qua4, I.qua5), and Quality innovation (i.quan1, i.quan2). Third Structural model also supports the existence of 3 dimensions in
performance variable:financial,process,and internalperformance.The idea that corporate performance has a multidimensional
nature consisting of financial and non-financial measures is consistent with prior research. Specifically, our financial dimension
performance (items perf1, perf2 and perf3 in Appendix A) is similar to financial perspective proposed in the Balanced Score Car
(BSC) by Kaplan and Norton (1996),and model of effectiveness based on rational goal by Quinn and Rohrbaugh (1983).Process
dimension in our measure of performance (items Perf4, Perf 5, Perf 6 and Perf 7) combines customer and internal perspectives
BSC, and the internal process model by Quinn and Rohrbaugh (1983). Finally, our internal dimension of performance (items Per
Perf 9 and Perf 10) is similar to learning and growth perspective by Kaplan and Norton (1996), and the human relations model o
effectiveness of 1983. Moreover, the 3 dimensions of performance found here (financial, process, and internal) are also alike di
components of diverse Intellectual Capital models. Thus, our valid, reliable scale for measuring performance can also contribute
academics and researches on corporate performance. The structural model supports the direct effects of the production, integr
and application of Knowledge as knowledge management constructs on seep and quality innovation. The effects of production a
Integration of knowledge on quality innovation is direct and significant. The application of knowledge effect on quality innovatio
directly but not significant. The production, integration and application of knowledge and quality, quantity and speed innovation
direct and significant effects on performance. The results deduced according to the statistics are calculated. The effects of 14 p
are > 1.69 and the effect ofone path is < 1.69.Therefore,fourteen hypotheses were supported and verified.Fig. 1. shows the
research model.
5.3. The test of the hypothesis
Based on the structural equation model results by partial least square method, research hypotheses were supported. For H1
and H3, we found that production, integration, and application of knowledge have a direct and significant effect on speed innov
The results are as follow:
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.208
10.516
0.513
0.000
K PRO I SPE
K PRO I SPE
1
. , .
. , . (H1)
Fig. 1. The relationship between exogenous components and Endogenous components.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
20

⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.198
10.123
0.481
0.000
K ITE I SPE
K INT I SPE
2
. , .
. , . (H2)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.178
8.053
0.440
0.000
K APP I SPE
K APP I SPE
3
. , .
. , . (H3)
Based on the above review,T-Values are > 1.96 and 2.58,also Pearson Correlation Values shows p < 0.05 and p < 0.01.
Therefore, hypotheses H1, H2 and H3 were supported. The determination coefficient of model shows that approximately 28% o
speed variations of innovation are justified by the production,integration,and application of knowledge,and 11%,9%, 8% are
allocated to them respectively.
For H4, H5 and H6, we found that the production, integration, and application of knowledge has a direct and significant effect
quality innovation. The results are as follow:
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.515
7.072
0.654
0.000
K PRO I QAU
K PRO I QAU
4
. , .
. , . (H4)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.126
2.099
0.556
0.000
K ITE I QAU
K INT I QAU
5
. , .
. , . (H5)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.065
0.764
0.518
0.000
K APP I QAU
K APP I QAU
6
. , .
. , . (H6)
Based on the above review, T-Values for hypothesis H4 is > 1.96 and 2.58. T-Values for hypotheses H5 and H6 are > 1.96. A
Pearson Correlation Values shows p < 0.05 and p < 0.01. Therefore, hypotheses H4, H5 and H6 were supported. The determina
Coefficientof modelshows thatapproximately 44% ofthe quality variations ofinnovation are justified by the production,in-
tegration, and application of knowledge, and 34%, 7%, 3% are allocated to them respectively.
For H7, H8 and H9, we found that the production, integration, and application of knowledge has a direct and significant effec
quantity innovation. The results are as follow:
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.161
7.645
0.396
0.000
K PRO I QAUN
K PRO I QAUN
7
. , .
. , . (H7)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.157
6.846
0.386
0.000
K ITE I SPE
K INT I SPE
8
. , .
. , . (H8)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.130
5.542
0.319
0.000
K APP I QAUN
K APP I QAUN
9
. , .
. , . (H9)
Based on the above review, T-Values are > 1.96 and 2.58 and also Pearson Correlation Values shows p < 0.05 and p < 0.01.
Therefore, hypotheses H7, H8 and H9 were supported. The determination Coefficient of model shows that approximately 17% o
quantity variations of innovation are justified by the production,integration,and application of knowledge,and 6%,6%, 4% are
allocated to them respectively.
For H10, H11 and H12, we found that the production, integration, and application of knowledge has a direct and significant e
on performance. The results are as follow:
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.187
23.158
0.705
0.000
K PRO PERF
K PRO PERF
10
. ,
. , (H10)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.176
19.824
0.662
0.000
K ITE PERF
K INT IPERF
11
. ,
. , (H11)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.157
18.242
0.592
0.000
K APP PERF
K APP PERF
12
. ,
. , (H12)
Based on the above review, T-Values are > 1.96 and 2.58 and also Pearson Correlation Values shows p < 0.05 and p < 0.01.
Therefore, hypotheses H10, H11 and H12 were supported. The determination Coefficient of model shows that approximately 64
the performance variationsare justified by the production ofknowledge,The Integration of Knowledge,The Application of
Knowledge,speed innovation,quality innovation,and quantity innovation.13%, 12%, 9% are allocated to the production of
knowledge, The Integration of Knowledge and The Application of Knowledge respectively.
For H13, H14 and H15, we found that speed innovation, quality innovation and quantity innovation has a direct and significa
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
21

effect on performance. The results are as follow:
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.156
13.471
0.586
0.000
I SPE PERF
I SPE PERF
13
. ,
. , (H13)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.193
23.284
0.726
0.000
I QAU PERF
I QAU PERF
14
. ,
. , (H14)
⎧
⎨
⎩
<
> ⇒ ⎧
⎨⎩
=
=
=
=
H H β
H β
β
T AND R
P
: 0: 0
1: 0
0.134
12.519
0.503
0.000
I QAUN PERF
I QAUN PERF
15
. ,
. , (H15)
Based on the above review, T-Values are > 1.96 and 2.58 and also Pearson Correlation Valuesshows p < 0.05 and
p < 0.01.Therefore,hypotheses H13,H14 and H15 were supported.The determination Coefficient of model shows that approxi-
mately 64% of the performance variations are justified by the production of knowledge, The Integration of Knowledge, The App
cation of Knowledge, speed innovation, quality innovation and quantity innovation. 9%, 14%, 7% are allocated to speed innovat
quality innovation and quantity innovation respectively.
6. Conclusions
This paper represents conclusions relevant to academics and practitioners. Our research finds and explains the dimension o
that improves organizational innovation and performance. Empirical evidence is provided about the consequences of the produ
of knowledge,The Integration of Knowledge and The Application of Knowledge on innovation and performance.It also develops
previous researches in the field of KM, where with a few empirical support, this link was proposed. Now, academics and compan
are aware of the implications and dimensions of KM. Thus, one of the main conclusions of this research is finding KM as a signifi
mechanism to enhance innovation and performance.Managers can use these findings to negotiate with stakeholders aboutim-
plementing KM projects. This research can contribute to practitioners, since it provides organizations with new insights and find
that managers can translate into their own companies. By now, firms which implemented KM programs, were unaware of its uti
and consequences (Moffett et al., 2002). Now, enterprises can learn about the positive impact of KM and its dimension on innov
and performance. Specifically, companies know that with a clear KM program they can be more innovative, achieve better finan
results,improve processes and develop human resources'capabilities.And, in turn, those benefits foster the link ofinnovation-
performance.
This research also has some limitations.First, the sample was obtained from the members of Iranian power syndicate.In this
sense, findings may be extrapolated to other areas or countries. Therefore, we cannot provide an international perspective for
above issue. However, in future research, a sampling frame that combines firms from different countries could be used in order
provide a more international perspective to the subject. Also, it may be interesting to analyze companies in different periods of
to observe their advances in KM and the existence of a KM implementation lifecycle. Initially, different KM program are expecte
time. Third, subjective measures for performance were included in the questionnaire.In future studies,we will consider objective
measures for performance such as intermediate outcomes of KM program (e.g. learning outcomes).
Appendix A
A.1. Production of knowledge (k.pro)
- External knowledge acquisition:
Specific staff in my workplace are responsible for obtaining knowledge from external Sources,
My work output relies on knowledge input externally.
Experienced staff are recruited externally.
- Internal knowledge acquisition:
Job rotation is encouraged in my Workplace.
Experienced staff and staff approaching departure are invited to record their knowledge and experience.
I learn lessons after project closure.
- Knowledge creation:
I am encouraged to find alternative solutions for existing assignments in my workplace.
Work-related suggestions are encouraged in my workplace.
Existing knowledge is used to develop new knowledge in my workplace.
I am encouraged to identify best practice for future use.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
22

I am encouraged to analyze success factors to enrich my knowledge.
I am encouraged to analyze mistakes to enrich my knowledge.
A.2. Integration of Knowledge (k.int)
- Knowledge storage:
Data and information are selected and organized before being stored in my workplace.
Knowledge is recorded by electronic tools (soft copy) in my workplace.
Knowledge is recorded in paper medium (hard copy) in my workplace.
Knowledge resides in human memory (minds) in my workplace.
Knowledge is kept in personal reference file(s).
Knowledge resides in my organization's routines/procedures.
Knowledge is recorded in the form of documentation such as office manuals, work practice, in-house standards, lessons lear
etc.
Confidential/sensitive information has restricted access in my workplace.
Access to some knowledge is recorded.
I know where to find knowledge when I need it.
I know who to ask for knowledge when I need it.
- Knowledge distribution:
Experienced staff in my workplace is encouraged to mentor new or less experienced staff.
Knowledge gained from different projects is made accessible to all in my workplace.
Knowledge is transferred by electronic means throughout the office.
Knowledge is distributed through documentation in my workplace.
Knowledge is shared by daily interaction with colleagues in the workplace, e.g. in the corridor, during lunch, in the pantry, at
social functions.
Knowledge is transferred by face-to-face means only.
Staffs who share knowledge receive rewards/recognition in my workplace.
The office layout in my workplace encourages staff to share knowledge.
Knowledge sharing is a measure of employees'performance in my workplace.
Remote access to the workplace's database is provided.
Staff with specific expertise is assigned to specific project(s)
A.3. Application of Knowledge (k.app)
- Knowledge use:
I utilize knowledge to solve most problems that I encounter in my job.
I am encouraged to apply knowledge/experience learned from previous project(s) to subsequent project(s).
I apply knowledge in developing new products/services.
- Knowledge maintaining:
Specific staff in my workplace are responsible for regular updating of knowledge in the database/library.
Specific staff in my workplace are responsible for maintaining the applicability of the knowledge in the database/library.
I am able to obtain the necessary knowledge when I need it.
A manager/senior staff member is assigned to deal with knowledge needs.
There is a clear policy/strategy in my workplace of how to handle knowledge.
A.4. Innovation speed (i.spe)
Our organization is quick in coming up with novel ideas as compared to key competitors.
Our organization is quick in new product launching as compared to key competitors.
Our organization is quick in new product development as compared to key competitors.
Our organization is quick in new processes as compared to key competitors.
Our organization is quick in problem solving as compared to key competitors.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
23

A.5. Innovation quality (i.qua)
Our organization does better in coming up with novel ideas as compared to key competitors.
Our organization does better in new product launching as compared to key competitors.
Our organization does better in new product development as compared to key competitors.
Our organization does better in processes improving as compared to key competitors.
Our organization does better in management improving as compared to key competitors.
A.6. Innovation quantity (i.quan)
The number of new or improved products and services launched to the market is superior to the average in your industry.
The number of new or improved processes is superior to the average in your industry.
A.7. Firm performance (perf)
Compared with key competitors, your company.
Firm performance is growing faster.
Firm performance is more profitable.
Firm performance achieves higher customer satisfaction.
Firm performance provides higher quality products.
Firm performance is more efficient in using resources.
Firm performance has internal processes oriented to quality.
Firm performance delivers orders quicker.
Firm performance has more satisfied employees.
Firm performance has more qualified employees.
Firm performance has more creative and innovative employees.
References
Adamides, E. D., & Karacapilidis, N. (2006). Information technology support for the knowledge and social processes of innovation management. Technovation
50–59.
Alavi, M., & Leidner, D. E. (2001). Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Q
25, 107–136.
Allocca, M. A., & Kessler, E. H. (2006). Innovation speed in small and medium sized enterprises. Creativity and Innovation Management, 15, 279–295.
Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82, 1
Bilton, C., & Cummings, S. (2009). Creative strategy: From innovation to sustainable advantage. John Wiley & Sons Ltd.
Borghini, S. (2005). Organizational creativity: Breaking equilibrium and order to innovate. Journal of Knowledge Management, 9(4), 19–33.
Boyd, J. L., & Bresser, R. K. (2008). Performance implications of delayed competitive responses: Evidence from the US retail industry. Strategic Management J
29(10), 1077–1096.
Brentani, U. (2001). Innovative versus incremental new business services: Different keys for achieving success. Journal of Product Innovation Management, 1
Brockman, B. K., & Morgan, R. M. (2003). The role of existing knowledge in new product innovativeness and performance. Decision Sciences, 34, 385–419.
Brown, J. S., & Duguid, P. (1991). Organizational learning and communities-of-practice: toward a unified view of working, learning, and innovation. Organizatio
Science, 2, 40–57.
Calantone, R. J., Cavusgil, S. T., & Zhao, Y. S. (2002). Learning orientation, firm innovation capability, and firm performance. Industrial Marketing Managemen
515–524.
Carbonell, P., & Escudero, A. I. R. (2010). The effect of market orientation on innovation speed and new product performance. Journal of Business & Industrial
Marketing, 25, 501–513.
Carbonell, P., & Rodriguez, A. I. (2006). The impact of market characteristics and innovation speed on perceptions of positional advantage and new product p
formance. International Journal of Research in Marketing, 23, 1–12.
Carbonell, P., & Rodriguez-Escudero, A. I. (2009). Relationships among team's organizational context, innovation speed, and technological uncertainty: An em
analysis. Journal of Engineering and Technology Management, 26, 28–45.
Carter, C., & Scarbrough, H. (2001). Towards a second generation of KM? The people management challenge. Education and Training, 43, 215–224.
Chen, M. J., & Hambrick, D. C. (1995). Speed, stealth, and selective attack: How small firms differ from large firms in competitive behavior. The Academy of
Management Journal, 38, 453–482.
Choi, B., & Lee, H. (2002). Knowledge management strategy and its link to knowledge creation process. Expert Systems with Applications, 23(3), 173–187.
Choi, B., & Lee, H. (2003). An empirical investigation of KM styles and their effect on corporate performance. Information Management, 40(5), 403–417.
Choy, C. S., Yew, W. K., & Lin, B. (2006). Criteria for measuring KM performance outcomes in organisations. Industrial Management & Data Systems, 106(7), 9
Civi, E. (2000). Knowledge management as a competitive asset: A review. Marketing Intelligence & Planning, 18(4), 166–174.
Clifton, N., Keast, R., Pickernell, D., & Senior, M. (2010). Network structure, knowledge governance, and firm performance. Evidence from innovation networks
SMEs in the UK. Growth and Change, 41, 337–373.
Coombs, R., & Hull, R. (1998). Knowledge management practices'and path-dependency in innovation. Research Policy, 27, 237–253.
Cui, A. S., Griffith, D. A., & Cavusgil, S. T. (2005). The influence of competitive intensity and market dynamism on knowledge management capabilities of MNC
subsidiaries. Journal of International Marketing, 13(3), 32–53.
Daft, R. L. (1982). Bureaucratic versus non-bureaucratic structure and the process of innovation and change. In S. R. Bacharach (Ed.). Research in the sociolo
organizations. JAI: Greenwich, CT.
Damanpour, F. (1991). Organizational innovation: A meta analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555–5
Damanpour, F., & Evan, W. M. (1984). Organizational innovation and performance: The problem of organizational lag. Administrative Science Quarterly, 29(3)
392–409.
Darroch, J. (2005). Knowledge management, innovation and firm performance. Journal of Knowledge Management, 9, 101–115.
Darroch, J., & McNaughton, R. (2002). Examining the link between knowledge management practice and types of innovation. Journal of Intellectual Capital, 3,
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
24

210–222.
Davenport, T. H., De Long, D. W., & Beers, M. C. (1997). Building Successful Knowledge Management Projects. January. Center for Business Innovation Workin
Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston: Harvard Business School Press.
DeTienne, K. B., & Jackson, L. A. (2001). Knowledge management; understanding theory and developing strategy. Competitiveness Review, 11(1), 1–11.
Dewar, R. D., & Dutton, J. E. (1986). The adoption of radical and incremental innovations: An empirical analysis. Management Science, 32, 1422–1433.
Dosi, G. (1988). Sources, procedures, and microeconomic effects of innovation. Journal of Economic Literature, 26, 1120–1171.
Drucker, P. F. (1993). Managing for the future: The 1990s and beyond. New York: Truman Talley Books/Plume.
Ettlie, J. E., Bridges, W. P., & O'Keffe, R. D. (1984). Organizational strategy and structural differences for radical vs. incremental innovation. Management Scie
682–695.
Fong, P. S. W., & Choi, S. K. Y. (2009). The processes of knowledge management in professional services firms in the construction industry: a critical assessm
theory and practice. Journal of Knowledge Management, 13(2), 110–126.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research
39–50.
Freeman, C. C. (1992). The economics of industrial innovation. Cambridge, MA: MIT Press.
Galunic, D. C., & Rodan, S. (1998). Resource recombinations in the firm: knowledge structuresand the potential for Schumpeterian innovation. Strategic Mana
Journal, 19, 1193–1201.
Gehlen, A. (1980). Man in the age of technology. New York: Columbia University Press.
Gloet, M., & Terziovski, M. (2004). Exploring the relationship between knowledge management practices and innovation performance. Journal of Manufacturin
Technology Management, 15(5), 402–409.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Sys
18(1), 185–214.
Grant, R. M. (1996). Towards a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122.
Gupta, A. K., & Govindarajan, V. (2000). Knowledge management's social dimension: lessons from Nucor steel. Sloan Management Review Fall, 2000, 71–80.
Hair, J., Anderson, R., Tatham, R., & Black, W. (2001). Análisis multivariante (5a ed.). Madrid: Prentice Hall.
Hall, R., & Andriani, P. (2002). Managing knowledge for innovation. Long Range Planning, 35, 29–48.
Hall, B. H., & Mairesse, J. (2006). Empirical studies of innovation in the knowledge-driven economy. Economics of Innovation and New Technology, 15, 289–29
Haner, U. E. (2002). Innovation quality—A conceptual framework. International Journal of Production Economics, 80, 31–37.
Hargadon, A. B. (1998). Firms as knowledge brokers: Lessons in pursuing continuous innovation. California Management Review, 40, 209–227.
Heirman, A., & Clarysse, B. (2007). Which tangible and intangible assets matter for innovation speed in start-ups? Journal of Product Innovation Management,
303–315.
Holsapple, C. W., & Jones, K. (2004). Exploring primary activities of the knowledge chain. Knowledge and Process Management, 11(3), 155–174.
Holsapple, C. W., & Jones, K. (2005). Exploring secondary activities of the knowledge chain. Knowledge and Process Management, 12(1), 3–31.
Hoque, Z., & James, W. (2000). Linking balanced scorecard measures to size and market factors: Impact on organizational performance. Journal of Manageme
Accounting Research, 12(1), 1–17.
Hsueh, L., & Tu, Y. (2004). Innovation and the operational performance of newly established small and medium enterprises in Taiwan. Small Business Econom
99–113.
Huergo, E. (2006). The role of technological management as a source of innovation: evidence from Spanish manufacturing firms. Research Policy, 35, 1377–1
Huseman, R. C., & Goodman, J. P. (1998). Leading with knowledge: The nature of competition in the 21st century. Thousand Oaks, CA, USA: Sage Publications
Jaffe, A. B. (1986). Technological opportunity and spillovers of R&D: Evidence from firm's patent profits and market value. American Economic Review, 76, 98
Jang, S., Hong, K., Woo Bock, G., & Kim, I. (2002). Knowledge management and process innovation: The knowledge transformation path in Samsung SDI. Journ
Knowledge Management, 6(5), 479–485.
Jaworski, B. J., & Kohli, A. K. (1993). Market orientation: Antecedents and consequences. Journal of Marketing, 57(3), 53–70.
Jenny, D. (2005). Knowledge management, innovation and firm performance. Journal of Knowledge Management, 9, 101.
Johnson, B. (1992). Institutional learning. In B.-A. Lundvall (Ed.). National systems of innovation (pp. 23–45). London: Pinter.
Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75–85.
Kessler, E. H., & Bierly, P. E., III (2002). Is faster really better? An empirical test of the implications of innovation speed. IEEE Transactions on Engineering Man
49, 2–12.
Kessler, E. H., & Chakrabarti, A. K. (1996). Innovation speed: A conceptual model of context, antecedents, and outcomes. The Academy of Management Revie
1143–1191.
Kline, R. B. (2010). Principles and practice of structural equation modeling. The Guilford Press.
Kogut, B., & Zander, U. (1996). What firms do? Coordination, identity, and learning. Organization Science, 502–518.
Kor, Y. Y., & Mahoney, J. T. (2004). Edith Penrose's (1959) contributions to the resource based view of strategic management. Journal of Management Studies
183–191.
Lahiri, N. (2010). Geographic distribution of R&D activity: How does it affect innovation quality? The Academy of Management Journal (AMJ), 53, 1194–1209.
Lanjouw, J. O., & Schankerman, M. (2004). Patent quality and research productivity: Measuring innovation with multiple indicators. The Economic Journal, 114
441–465.
Lee, H., & Choi, B. (2003). Knowledge management enablers, processes, and organizational performance: An integrative view and empirical examination. Jou
Management Information Systems, 20, 179–228.
Leonard, D., & Sensiper, S. (1998). The role of tacit knowledge in group innovation. California Management Review, 40(3), 112–132.
Levinthal, D., & March, J. (1993). The myopia of learning. Strategic Management Journal, 14, 95–112.
Liao, C., & Chuang, S. H. (2006). Exploring the role of knowledge management for enhancing firm's innovation and performance. Proceedings of the 39th Haw
International Conference on System Sciences, Hawaii.
Liao, C. C., Wang, H. Y., Chuang, S. H., Shih, M. L., & Liu, C. C. (2010). Enhancing knowledge management for R&D innovation and firm performance: An integ
view. African Journal of Business Management, 4, 3026–3038.
Liebeskind, J. P. (1997). Keeping organizational secrets: protective institutional mechanisms and their costs. Industrial and Corporate Change, 6, 623–663.
Majchrzak, A., Cooper, L. P., & Neece, O. E. (2004). Knowledge reuse for innovation. Management Science, 50(2), 174–188.
Mansfield, E. (1968). Industrial research and technical innovation. New York: Norton.
March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87.
Massey, A. P., Montoya-Weiss, M. M., & O'Driscoll, T. M. (2002). Knowledge management in pursuit of performance: Insights from Nortel networks. MIS Quarte
26(3), 269–289.
McKeen, J. D., Zack, M. H., & Singh, S. (2006). Knowledge management and organizational performance: An exploratory survey. Proceedings of the 39th annu
internationalconference on systems sciences (pp. 1–9). .
Michailova, S., & Husted, K. (2003). Knowledge-sharing hostility in Russian firms. California Management Review, 45(3), 59–77.
Moffett, S., McAdam, R., & Parkinson, S. (2002). Developing a model for technology and cultural factors in knowledge management: A factor analysis. Knowle
Process Management, 9(4), 237–255.
Mokyr, J. (1990). The level of riches: Technological creativity and economic progress. Oxford: Oxford University Press.
Ng, P. T. (2009). Relating quality and innovation: an exploration. International Journal of Quality and Innovation, 1, 3–15.
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37.
Nonaka, I., & Takeuchi, H. (1995). The Knowledge-creating Company How Japanese Companies Create the Dynamics of Innovation (first ed.). Oxford: Oxford U
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
25

Press.
Nonaka, I., Toyama, R., & Konno, N. (2000). SECI Ba and leadership. Long Range Planning, 33, 5–34.
Parasuraman, A. (2010). Service productivity, quality and innovation: Implications for service-design practice and research. International Journal of Quality an
Sciences, 2, 277–286.
Penrose, E. T. (1959). The Theory of the Growth of the Firm. New York: John Wiley.
Pentland, B. T. (1995). Information systems and organizational learning: The social epistemology of organizational knowledge systems. Accounting, Managem
Information Technologies, 5, 1–21.
Probst, G., Raub, S., & Romhardt, K. (1999). Wissen managen. Wie Unternehmen ihrewertvollste Ressource optimal nutzen, first ed. Gabler: Frankfurt am Mai
Quinn, R. E., & Rohrbaugh, J. (1983). Aspatial model of effectiveness criteria: Towards a competing values approach to organizational analysis. Management S
29(3), 363–377.
Robinson, W. T. (1990). Product innovation and start-up business market share performance. Management Science, 36, 1279–1289.
Sadikoglu, E., & Zehir, C. (2010). Investigating the effects of innovation and employee performance on the relationship between total quality management pr
and firm performance: An empirical study of Turkish firms. International Journal of Production Economics, 127, 13–26.
Salojärvi, S., Furu, P., & Sveiby, K. E. (2005). Knowledge management and growth in Finnish SMEs. Journal of Knowledge Management, 9(2), 103–122.
Schumpeter, J. A. (1935). Theorie der wirtschaftlichen Entwicklung (fourth ed.). München and Leipzig: Duncker & Humblot.
Sher, P., & Lee, V. (2004). Information technology as a facilitator for enhancing dynamic capabilities through knowledge management. Information Manageme
933–945.
Singh, J. (2008). Distributed R&D, cross-regional knowledge integration and quality of innovative output. Research Policy, 37, 77–96.
Skyrme, D. (2001). Capitalizing on knowledge: From e-business to k-business. Oxford: Butterworth-Heinemann.
Slater, S. F., & Mohr, J. J. (2006). Successful development and commercialization of technological innovation: Insights based on strategy type. Journal of Produ
Innovation Management, 23, 26–33.
Smith, A. D. (2011). Competitive approaches to new product development: A comparison of successful organizations in an unstable economic environment. T
Performance Management, 17, 124–145.
Storey, C., & Kahn, K. (2010). The role of knowledge management strategies and task knowledge in stimulating service innovation. Journal of Service Researc
397–410.
Subramaniam, M., & Youndt, M. A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Review, 48, 4
Swan, J., Newell, S., & Robertson, M. (1999). Limits of IT-driven knowledge management for interactive innovation processes: Towards a community-based ap
Proceedings of 33rd HICSS.
Swan, J., Newell, S., Scarbrough, H., & Hislop, D. (1999). Knowledge management and innovation: networks and networking. Journal of Knowledge Manageme
262–275.
Tatikonda, M. V., & Montoya-Weiss, M. M. (2001). Integrating operations and marketing perspectives of product innovation: The influence of organizational pr
factors and capabilities on development performance. Management Science, 151–172.
Teece, D. J. (1989). Inter-organizationalrequirements of the innovation process.
Teece, D. J. (2000). Strategies for managing knowledge assets: the role of firm structure and industrial context. Long Range Planning, 33, 35–54.
Teece, D. J., & Pisano, G. (1994). The dynamic capabilities of firms: an introduction. Industrial and Corporate Change, 3(3), 537–556.
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.
Thomas, K., & Keithley, T. (2002). Knowledge management improves performance. AACE International Transactions, PM.17.1–PM.17.24.
Tidd, J., Bessant, J., & Pavitt, K. (2001). Managing Innovation – Integrating Technological Market and Organizational Change (second ed.). New York: John Wile
Tidd, J., Bessant, J. R., & Pavitt, K. (2005). Managing innovation: Integrating technological, market and organizational change. John Wiley & Sons Inc.
Tseng, S. M. (2008). Knowledge management system performance measure index. Expert Systems with Applications, 34(1), 734–745.
Tseng, C. Y., & Wu, L. Y. (2007). Innovation quality in the automobile industry: Measurement indicators and performance implications. International Journal of
Technology Management, 37, 162–177.
Utterback, J. M., & Abernathy, W. J. (1975). A dynamic model of process and product innovation. Omega, 3(6), 639–656. Managerial and Decision Economics,
35–42(special issue).
Vaccaro, A., Parente, R., & Veloso, F. M. (2010). Knowledge management tools, inter organizational relationships, innovation and firm performance. Technological
Forecasting and Social Change, 77(7), 1076–1089.
Wang, C. L., & Ahmed, P. K. (2004). The development and validation of the organizational innovativeness construct using confirmatory factor analysis. Europe
Journal of Innovation Management, 7(4), 303–313.
Wiig, K. M. (1997). Knowledge management: where did it come from and where will it go? Expert Systems with Applications, 13, 1–14.
Wu, I., & Lin, H. (2009). A strategy-based process for implementing knowledge management: An integrative view and empirical study. Journal of the American
for Information Science and Technology, 60(4), 789–802.
Yang, J. (2005). Knowledge integration and innovation: Securing new product advantage in high technology industry. Journal of High Technology Management
16, 121–135.
Yang, J. (2010). The knowledge management strategy and its effect on firm performance: A contingency analysis. International Journal of Production Economi
215–223.
Zack, M. H. (1999). Developing a knowledge strategy. California Management Review, 41(3), 125–145.
Zaltman, G., Duncan, R. L., & Holbek, J. (1973). Innovations and organizations. New York: Wiley.
A. Mardani et al. Journal of High Technology Management Research 29 (2018) 12–26
26