ASAC 2007 Martin Spraggon, ABD Ottawa, Ontario Administrative Science Department University ...

21 Pages·2007·0.17 MB·English

ASAC 2007 Martin Spraggon, A.B.D.
Ottawa, Ontario Administrative Science Department
University of Quebec in Outaouais

Virginia Bodolica, Ph.D.
Industrial Relations Department
University of Quebec in Outaouais
KNOWLEDGE CREATION PROCESSES IN SMALL INNOVATIVE HI-TECH FIRMS
Although knowledge creation is viewed as fundamental for securing a firm’s
competitive advantage by scholars of strategic management and
organizational learning (Nonaka, 1994; Nonaka and Takeuchi, 1995;
Prahalad and Hamel, 1990; Nelson 1990; Leonard-Barton, 1992; Teece,
2005), few studies have systematically investigated the specific knowledge
creation processes put in place by small hi-tech firms (Desouza and Awazu,
2006). The objective of this paper is to systematically explore knowledge
creation processes in small hi-tech firms operating in the software industry.

Introduction

In order to survive and remain competitive, small hi-tech firms necessitate creating and
rejuvenating knowledge endlessly (Brown and Eisenhardt, 1997). Knowledge has become an essential
source of value creation and sustainable competitive advantage (Teece, 2005; Nonaka and Takeuchi,
1995). The ability of small hi-tech firms to create knowledge relentlessly and manage it strategically is
viewed as critical to organizational success (Inkpen and Dinur, 1998; Nonaka and Teece, 2001; Desouza
and Awazu, 2006).
Although knowledge creation is viewed as fundamental for securing a firm’s competitive
advantage by scholars of strategic management and organizational learning (Nonaka, 1994; Nonaka and
Takeuchi, 1995; Prahalad and Hamel, 1990; Nelson 1990; Leonard-Barton, 1992; Teece, 2005), few
studies have systematically investigated the specific knowledge creation processes put in place by small
hi-tech firms (Desouza and Awazu, 2006). The objective of this paper is to explore knowledge creation
processes in five small hi-tech firms operating in the software industry.
The paper is organized as follows. The next section provides a brief literature review on
knowledge and knowledge creation. We continue by explaining the research methodology adopted in this
study. An in-depth analysis of the cross-case findings follows. We conclude the paper with a detailed
discussion of our results in the light of extant literature.

Literature review
Knowledge
Knowledge has become an essential source of value creation and innovation (Schüppel, Müller-
Stewens, and Gomez, 1998). Many authors agree on the extent to which organizational knowledge and
related organizational learning processes, such as knowledge creation, are core elements of innovative
firms (Nonaka, 1994; Tsoukas and Vladimirou, 2001; McEvily and Chakravarthy, 2002; Kim, 1993;
Tsoukas, 1996; Crossan and Bedrow, 2003; Inkpen and Tsang, 2005). Nonaka (1994) affirms that
knowledge has become the most important input for innovation activities. Innovation generation demands
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that knowledge be continually renewed and replenished (Brown and Eisenhardt, 1997; Lane and
Lubatkin, 1998; Crossan and Bedrow, 2003).
Nonaka (1994) defines knowledge as a “multifaceted concept with multilayered meanings”. The
author considers knowledge to be a “justified true belief”, or a “personal belief” that increases an
organization’s capacity for effective action (Nonaka & Takeuchi, 1995). This definition conceives
knowledge as a dynamic human process of “justifying personal beliefs as a part of an aspiration for the
truth”. Spiegler (2000) defines knowledge as “the power to act and to make value-producing decisions”.
Davenport and Prusak (1998) define knowledge as “a flux mix of framed experiences, values, contextual
information, and expert insight that provides a framework (outcome) for evaluating and incorporating
new experiences and information (processes).” Knowledge is dynamic, relational, and based on human
action.
Based on the seminal work of Polanyi (1967), Nonaka and Takeuchi (1995) identify two types of
knowledge: “tacit” and “explicit”. Explicit knowledge refers to codified knowledge, which is easily
transmitted in a formal, explicit, and systematic language. Tacit knowledge refers to knowledge that
remains much harder to transfer, formalize or codify, due to its “personal” quality. Tacit knowledge as
opposed to explicit is deeply rooted in action, commitment, and involvement in a specific situation or
context (Nonaka 1994; Tsoukas and Vladimirou, 2001) and involves cognitive and technical components.
The cognitive component is related to an individual’s “mental model” of the world (Polanyi, 1966), while
the technical element refers to concrete know-how and skills applied to specific situations (Brown and
Duguid, 1991).
Knowledge creation
The creation of new organizational knowledge is increasingly becoming a managerial priority,
particularly for small hi-tech firms operating in fast-moving environments. New knowledge provides the
basis for organizational renewal and sustainable competitive advantage (Prahalad and Hamel, 1990;
Crossan and Berdrow, 2003).
Knowledge is created by individuals (Nonaka and Takeuchi, 1995; Grant, 1996). Although ideas
are formed in the mind of individuals, interactions between individuals typically plays a significant role in
developing new ideas and creating new knowledge (Nonaka, 1994). Nonaka and Teece (2001) conceive
an organization as an entity that creates knowledge by virtue of its actions and interactions (Levinthal and
Myatt, 1994) with its environments.
Nonaka (1994) and Nonaka and Takeuchi (1995) developed one of the most influential theories of
organizational knowledge creation. These authors propose a “spiral model” of knowledge creation, which
explains the continual relationships between explicit and tacit knowledge. Explicit and tacit knowledge
are complementary and essential to knowledge creation. The interaction between these two types of
knowledge is called ‘knowledge conversion’. A firm creates new knowledge through the conversion and
interaction between its tacit and explicit knowledge. Understanding the reciprocal relationship between
these two kinds of knowledge would be the key to understand the knowledge-creating process.
Through this ‘conversion’ process, tacit and explicit knowledge increase in terms of quantity and
quality (Nonaka, 1994, Nonaka and Takeuchi, 1995, Nonaka and Teece 2001). Nonaka (1994) postulates
four types of knowledge conversion: (a) socialization, from tacit knowledge to tacit knowledge, (b)
externalization, from tacit knowledge to explicit knowledge, (c) combination, from explicit knowledge to
explicit knowledge, and (d) internalization, from explicit knowledge to tacit knowledge.
Knowledge is both explicit and tacit and effective knowledge creation depends on an enabling
context, called “Ba” (Nonaka and Teece, 2001). Ba is a boundless context shared by those who interact
with each other; through such interactions, participants and context - ba - evolve to create knowledge.
“Ba” can possess a physical, virtual, and mental dimension. Knowledge creation contexts might also be
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favored by a shared identity (Kogut and Zander, 1996), dense social capital (Nahapiet and Ghoshal,
1998), and trust (Das and Teng, 2000).
Nonaka and Teece (2001) argue that knowledge is also created in the “spiral” that goes through
pairs of seemingly antithetical concepts, such as order and chaos, micro and macro, part and whole, mind
and body, tacit and explicit, and creativity and control. In a similar vein, Brown and Eisenhardt (1997)
suggest that successful innovative firms blend limited structure around responsibilities and priorities with
extensive communication and design freedom in order to favor knowledge creation. This combination is
neither so structured that change cannot occur nor so unstructured that chaos ensues. This seems to be the
case with small hi-tech firms, where their ‘pendulous’ knowledge creation processes amalgamate
creative-chaotic and planned actions, explicit-formal-structured and tacit-informal-home-made procedures
and knowledge.

Methodology

This exploratory research is constituted by five case studies, each of them being represented by a
small Canadian software firm. To be eligible for the sample, firms needed to meet pre-established specific
requirements (see Exhibit 1). A case study allows the comprehension of complex social phenomena
because it takes into consideration the contextual conditions that remain extremely pertinent to the
phenomenon under investigation (Creswell, 1998; Stake, 1995). The five cases were chosen in a
purposeful fashion (Creswell, 2003) and for theoretical reasons (Eisenhardt, 1989). The rationale and
power behind purposeful sampling resides in selecting “information-rich cases”. Exploring information-
rich cases yields insights and in-depth understanding of the phenomena under study (Patton, 2002). The
research design is of the type “multiple-case study, with a holistic-one-unit of analysis” - knowledge
creation processes (Yin, 2003). Multiple-case studies’ outcomes are considered to be more compelling
and our overall research is therefore conceived as being more robust than a single case study.

Exhibit 1: Sample eligibility requirements
Sample requirements for eligibility
SSFs (cid:190) Canadian firm
(Small Software Firms) (cid:190) Software industry
(cid:190) ≤ 100 Employees
(cid:190) Main activity: conception, creation, development
Our analysis draws upon four sources of data: (a) in-depth interviews, (b) public documentation,
(c) archival records, and (4) direct observation. In each explored small hi-tech firm we gathered
information on the perspectives of two levels of the management hierarchy. The key informants included
among others the CEO (Chief Executive Officer), CTO (Chief Technology Officer), marketing VP (Vice-
President), product development VP, sales manager, project manager, and software programmers and
developers. A total of fifteen interviews (three per case) had been conducted and subsequently transcribed
and coded using qualitative software - NVIVO 07. Interviews typically lasted 90 minutes, although two of
them ran as long as two hours. After two month of intense work, we came up with 310 “nodes” that
permitted us to compare patterns, contexts, and knowledge creation processes across cases with a high
level of accuracy and transparency.
To evaluate knowledge creation processes and facilitate comparison across cases, we created a
“continuous seven-level scale” (see Brown, 1988, 2000). Such a scale allowed us assigning a level to each
explored knowledge creation process along a continuum of seven levels: “low”; “low/medium”;
“medium/low”; “medium”; “medium/high”; “high/medium”; and “high”. Along the continuum, “low”
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means that we found (almost) no evidence of a knowledge creation process and “high” means that the
process occurred in a highly intensive and frequent fashion (compared to the rest of the sample).
The seven levels are a function of comparison across cases. To categorize SSFs’ knowledge
creation processes into seven ‘levels’ we considered and evaluated such factors as the intensity, the
frequency, and the variance (among cases) of each explored knowledge creation process by juxtaposing
different sources of data (interviews, observations, and internal documents) related to each process (see
Inkpen and Dinur, 1998). Using qualitative software (Nvivo07) permitted us to create nodes and
accurately assess the “density of citations” and levels (i.e. “low, “low/medium”, “medium/low”, etc.) of
each studied knowledge creation process.
The sample firms’ and their technologies’ names are camouflaged in this paper in order to meet
the confidentiality requirements. The main characteristics of the five small hi-tech firms under
investigation are provided in Exhibit 2.
Exhibit 2 - Description of Sample SSFs

Firms’ name Nature of technology Founded Total employees
Alpha Web Applications 1997 50
Beta Security 2004 50
Gamma Voice-over-IP 2004 15
Delta Wireless Mesh System 2001 80
Epsilon Network 2003 100

Findings

Knowledge creation processes in small hi-tech firms
In order to innovate, all five studied SSFs are constantly creating information and knowledge with
the aim of ‘re-inventing’ their own environments. Our sample firms have developed and implemented
particular organizational settings and processes to support the creation of knowledge. What emerges from
our data is that knowledge creation occurs at the individual, group, organizational, and interorganizational
levels via two main processes: (1) ‘interaction,’ and (2) ‘action.’ While ‘interaction’ is related to
exchange and communication, ‘action’ is associated with the execution and implementation of
knowledge.
Knowledge creation through interaction
Knowledge is created by individuals, “It’ll often start with one developer having an idea or
an approach”, convey all SSFs’ interviewees. Although ideas are formed in the minds of individuals,
our data indicate that interactions between individuals, groups and organizations play a significant
role in developing new ideas. We found that continuous communication, exchange and interaction are
the keystones of knowledge creation in all explored SSFs. According to our data, interaction
promoting the creation of knowledge in SSFs can take place through: (1) Formal meetings; (2)
Informal communities (Communities of Practice (CoP), Communities of Sharing (CoS), Virtual
Communities (VC), or Informal Networks (IN); (3) Project teams (“within” and “across” teams); (4)
External interaction (customers and partners); and (5) IT-Tools (intranet).
Exhibit 3 “Knowledge creation processes through interaction in SSFs” synthesizes and
juxtaposes our findings and evidence related to the creation of knowledge through interaction
activities in all five SSFs.
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1. Formal Meetings
All five SSFs have put in place different kinds of formal meetings for creating and exchanging
information and knowledge. Alpha, Beta, and Gamma, for example, have “brainstorming sessions” which
are scheduled in advance and where all employees are generally invited to participate. The main goal of
these “brainstorming encounters” is to bring about new ideas freely, without judging them, in order to
solve specific problems related to the innovation process or to a new technology. The management teams
from Alpha, Beta and Gamma believe that brainstorming sessions are vital for the generation of new ideas
and knowledge.
Delta and Epsilon have developed other kinds of formal meetings to create knowledge. Delta’s
management team, for example, has put in place “short-intense teaching sessions” in order to exchange
and create new knowledge “rapidly and intensely,” says Delta’s Engineering VP. He explains, “…people
come up with an idea, they put it on paper, we get together in a room, and the person that created the
idea teaches to the rest of the group.” In the case of Epsilon, R&D and Marketing employees have
numerous formal reviews with their customers, such as product and specifications reviews, which permit
them to exchange, receive, absorb, and create new knowledge.
Overall, our data suggests that Alpha, Delta and Epsilon possess a “high” level of formal
meetings compared to Beta and Gamma, who exhibit a “medium” and “medium/low” level respectively.
This level classification may be explained by the fact that Delta and Epsilon have larger numbers of
employees compared to the other three SSFs and consequently need to implement more communication
and knowledge creation processes, such as formal meetings. Epsilon’s Marketing VP says, “When we
were 75 people we had to adapt even more processes. Knowledge management, I guess, it’s all about
implementing processes in a sense, right? You can’t have 75 people in total chaos.” Delta’s Engineering
VP explains, “Now we have more formal processes, but when we started, the first year and a half, there
was no time for that […]. We have these formal processes in place…but because we’re growing, we have
more people, we have 80 people instead of ten, and you can not be that disorganized and informal.”
Although Alpha has 50 employees, it also possesses a “high” level of formal meetings, like Delta
and Epsilon. Alpha’s high level of formal meetings can be explained by the fact that its management team
strongly believes that a company’s success is determined by the extent to which employees’ ideas are
formalized through formal and explicit processes. Alpha’s CEO states, “That [formalizing] is making
innovation less of an art, less of a wild thing […]. We seek to funnel the creativity of our people.”
Beta and Gamma show evidence of a “medium” and “medium/low” level of formal meetings. In
the case of Beta, the management team thinks it is common for start-ups to have few knowledge creation
processes in place, “…there are few codified processes in place where we do things as strictly or rigidly
as possible,” explains Beta’s Marketing VP. The company’s CTO posits, “…here, most things are tacit
and informal.” Gamma is the smallest firm of our sample in terms of number of employees, a fact that
might explain its “medium/low” level of formal meetings aiming at creating knowledge. From this
analysis, we may infer that the larger an organization is in terms of number of employees, the higher is its
level of formal meetings aiming at creating knowledge.
2. Informal Communities
According to all five SSFs’ management teams, knowledge creation also occurs via daily
informal interaction and spontaneous communication and exchange between employees, teams and
external partners. What emerges from our data is that that informal communities and networks are
continuously being formed and transformed within and across teams and departments. We have identified
four different informal communities throughout our interview data and observations: Communities of
Practice (CoP), Communities of Sharing (CoS), Virtual Communities (VC), and Informal Networks (IN).
“Communities of practice” are informal and spontaneous communities of people that share
common interests or goals and gather together in order to solve and tackle a given problem.
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“Communities of sharing” are formal or informal communities of people that gather together to share and
exchange ideas, information, and knowledge. “Virtual communities” are formal or informal communities
of people that share common interests, ideas, and knowledge over the Internet or other IT-tools. “Informal
networks” refer to informal, voluntary, and spontaneous relationships that are developed within an
organization among members and are not found in any organizational chart.
While Beta, Gamma and Epsilon present a “high” level of informal communities’ formation,
Alpha and Delta exhibit a “medium/high” level. Gamma represents a good example of informal
communities’ formation. At Gamma, all employees collaborate and interact closely and intensely in order
to provide their inputs to better understand and solve a given problem, regardless its nature. From
Gamma’s management team point of view, knowledge is created “informally, spontaneously and
collaboratively” via communities of practice and sharing, where all employees participate. Gamma’s
Engineering VP says, “That sort of ad hoc, I’d say, is how we get a lot of the technical problems solved.
‘I’m gonna do this!’‘ This is what I think the best solution is’. They’ll have thought about it [problem] on
their own and firmly presented it [to the team or whole organization].” Gamma’s Business Development
VP says, “It’ll often start with one developer having an idea or an approach, and then a solution is sort
of fielded by all of us.” Our data suggests that extensive informal communities and interaction among
employees makes it possible to solve specific problems and create new knowledge and ideas.
In the following passage, Gamma’s Engineering VP illustrates another community of practice’s
situation in which employees interact and collaborate spontaneously to solve an emergent problem.
“There’s a lot of informal stuff where someone will have a problem, and they’ll say, ‘what do you think
about this?’ ‘This is the solution I think’. ‘I have no idea how to solve this. I don’t know what to do’. ‘This
is the solution I think, what do you think?’ We’ll discuss and anyone else who is listening or has an
interest will just stand up. In this open place it’s really easy to have a half an ear, ‘oh yeah, I know
something about that, listen’.” Once a problem comes up, all of Gamma’s employees will delve into the
problem and give their points of view on how to tackle it. Knowledge is created via informal communities
and employees’ interaction.
At Epsilon, as with Gamma, communities of practice and sharing are common phenomena. The
formation of these informal communities are explained by the fact that more than half of Epsilon’s
employees have worked together in the past for other companies and know each other quite well. The
Product Development VP explains, “So, for example, you go into the lunchtime discussions any day, and
there’s a community of sharing…there is a big circle. You hear the discussions in there and they go
across the topics from user interfaces, usability, applications. So there's this powerful informal knowledge
transfer mechanism which is just…pure knowledge exchange.”
In the case of Beta, most communications are informal and internal informal networks are the
predominant interaction pattern. Beta’s CTO affirms, “The people that have a lot of knowledge, the
couple of brains, they are consulted as need be. It’s informal like that. When you need, you go to see
them. It’s just more of an informal network that way. That’s how we are running now that we are small.”
At lunch time, for example, employees often gather and informally exchange and share knowledge. “The
cafeteria area is so important. It’s like having a family lunch together; we bring pizza or something…just
to get people to come and all interact. And here you have culture going through interaction…knowledge
flows and grows,” illustrates the CTO.
Alpha and Delta also have informal communication and informal communities’ formation, but
not as extensive and frequent as in the case of Gamma, Epsilon, and Beta. Alpha’s CEO states “…we
have a lot of smart people here who are willing to talk about things and bounce ideas around all the
time.” At Alpha, as at Gamma, there are virtual communities of sharing. “We have an intranet site that
lets you publish everything, from a link to an article, and it lets other people either comment on that or
even change that article itself,” explains the CEO. However, Alpha’s CEO prefers not to rely on informal
communication or processes. “I feel very uncomfortable around things that…on things that I need to
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depend on that are informal…I’m not an organizational freak.” Delta exhibits the same level of informal
communities’ formation as Alpha. Delta’s CEO explains, “…teamwork, collaboration and ideas sharing
occur all the time, whether during work or lunch time.”
Overall, what emerges from our data is that informal communication and communities’
formation, regardless of its nature, are common phenomena in all five SSFs. We found that informal
communities enable and prompt individual, group and organizational learning, knowledge exchange, and
knowledge creation.
3. Project Teams
Our sample firms are formally structured in flexible and cross-functional project teams aiming at
achieving knowledge creation via intense and frequent complementary resource exchange,
communication and interaction. According to our data, organizing knowledge-workers into project teams
is a common pattern across the five cases. In all explored SSFs, project teams’ participants present a high
degree of empowerment, which permits them to interact, pool resources, and take action “freely” within
their teams. SSFs’ management teams agree on the extent to which employees create knowledge on a
daily basis through interaction “within” and “across” project teams.
3.1 Interaction “Within” Project Teams
What emerges from our data is that the five SSFs exhibit a “high” level of interaction “within”
project teams. SSFs’ project teams’ members spend most of the day working and collaborating together,
tackling specific problems, sharing stories and experiences, and exchanging knowledge and ideas within
their project teams. From the SSFs’ management teams’ point of view, all these social activities within
teams enable knowledge creation and flowing. Alpha’s CEO says, “Team collaboration creates
knowledge synergies and has a multiplier effect on knowledge creation.” Beta’s CTO affirms, “People
interact intensely within their teams.” Gamma’s Business Development VP conveys, “…we work closely
and the trade information back and forth.” Delta’s CEO posits that people are “living repositories of
knowledge talking to each other” so that knowledge creation and innovation occur recurrently via team
work. He also argues that teamwork makes it possible to “cross-fertilize knowledge from various different
people and create new knowledge.” Epsilon’s Marketing VP relates, “The team lab comes up with some
great ideas […]. They work very well together and create so much knowledge.”
3.2 Interaction “Across” Project Teams
Our data suggest that in terms of interaction “across” project teams, Gamma, Delta and Epsilon
present a “high” level of interaction. In the case of Gamma, for example, all 15 employees will work
together in order to resolve any given problem that emerges. Gamma’s Engineering VP explains, “…we
have fairly good discussions and just solve the problem all together”. Gamma’s Business Development
emphasizes, “…we work closely and we trade information back and forth within and across projects.”
Delta has implemented what they call “systems groups.” These groups are formed by highly
specialized programmers, “market thinkers,” and PhDs in mathematics. Although these highly skilled
knowledge-workers work vertically in their own departments and within their specialized teams, they are
often reallocated into “systems groups” in order to enhance knowledge exchange and prompt innovation
generation. At Delta, as at Gamma, project teams are considered to be “permeable, flexible and
interchangeable.” When designers, marketing people or software architects that work on a given project,
for example, are reallocated into another project, formally or informally, they bring with them a “new”
corps of knowledge into the new project team that makes it possible to generate novel insights and create
new knowledge through exchange and ‘transferability’. At Delta, resource reallocation across projects is
basically formal; at Gamma it occurs rather spontaneously. Delta’s Engineering VP argues, “System
groups…so if you combine both [teams], everything is possible! I think that’s how you succeed with
innovation.”
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Like Gamma and Delta, Epsilon also presents a “high” level of interaction across project teams.
Epsilon’s Product Development VP explains, “We put people with different backgrounds together in a
team and there is a synergy that happens where knowledge sharing comes together. I think that the
combination of different types of skills actually creates a new level of knowledge that you don’t have by
just having independent functions…mixing team, that’s important.” Epsilon’s CEO relates, “We have
people that specialize in usability. The will work formally and informally with all different teams.” At
Gamma, Delta, and Epsilon, knowledge is endlessly and freely flowing, being “re-used” and “re-
created” via interaction and new combinations within and across project teams.
Compared to those three SSFs, Alpha and Beta exhibited a “medium” level of interaction across
project teams. Alpha, for example, tends to keep some limits between teams due to its intellectual
property policy. Alpha’s CEO explains, “Each team can see the processes of others projects at the top,
the templates are there, but the implementation or the filling of that template may have some intellectual
property. So we have to keep China walls between teams.” He argues, “From the project, what we will
share will be our know-how; it will be what we’ve learned that works versus what didn’t work. It won’t be
IP related. You have to extract the essence, and the essence is not the implementation, the essence is the
meta-information let’s say.” Although there is some interaction and knowledge exchange across project
teams, certain specific content and knowledge are overprotected within teams.
Although Beta’s employees collaborate and exchange knowledge intensively, they tend to do it
within rather than across departments. Project teams are “pushed” to collaborate with each other by the
management team because they do not do so spontaneously or of their own accord. Beta’s CTO
explicates, “Each function in the company kind of has its own style. Sales people are managed on quite a
different way than developers are managed.” Moreover, there are several “clusters,” within departments
that have developed specific “microcultures.” “There are sections where we have one corner where we
kind of have our sales guys. And there is the section for product management, and another one for
developers. So if you walk around our building, you’ll find that there are these clusters with their own
codes,” explains the CTO.
The “cultural differences” between those clusters tend to be an obstacle to interaction across
project teams and departments. Beta’s CTO explains, “Sales is so foreign to development, those are part
of the two extremes. They’re very different people but they need to work with each other.” However, at
the management team’s level, there is a continuous interaction across departments’ VPs and directors.
This phenomenon may be explained by the fact that most management teams’ members have worked
together in the past. Beta’s Marketing VP posits, “I think the working relationships between the various
functional groups are as open as possible to make sure that there’s the ongoing dialogue. Part of that is
that a lot of us [management team] have worked together for years and years, so we have those natural
working relationships.”
To sum up, all five SSFs exhibited a “high” level of interaction within project teams. Intense
interaction within project teams allows participants to exchange, acquire, internalize, and learn new
knowledge and expand their base of expertise. Interaction across project teams enables an organization to
create new knowledge by “cross-fertilizing” knowledge bases from a variety of employees and
specialized teams. Our data suggest that previous relationships among employees may favor both within
and across project teams’ interaction. However, interaction across project teams is not always natural and
spontaneous. Factors such as teams’ cultural differences and organizational values might be an obstacle to
knowledge flow and interaction across project teams.
4. External Interaction
4.1 Customers
Since their very conception, Alpha, Gamma, Delta and Epsilon collaborate closely and intensely
with their customers throughout their product development projects. Our data suggest that Alpha,
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Gamma, Delta and Epsilon possess a “high” level of interaction with their customers while Beta exhibits
a “medium” level. Alpha’s Marketing VP says, “There’s a huge amount of collaboration that happens
with clients”. Epsilon’s CEO asserts, “By working together with our customer we’re getting real time
feedback. We truly know well in advance what pieces we need to do, and what we don’t need to do, so
that we’re not inefficient. That’s the main thing.” From Delta’s CEO point of view, “Customer’s
feedback loop is very very important. That’s why it is important to have customers and interact closely
with them, because you have to start from a concrete application down. According to Gamma’s Business
Development VP, “…get closer to the customer. They can be quite useful in learning about issues that
may be affecting the industry.”
From these four SSFs’ management teams’ point of view, customers represent a significant
source of inspiration, new ideas, and innovation. Lead customers, they explain, can reveal new uncharted
product needs that might trigger new technology trajectories. Epsilon’s CEO, for example, affirms that
co-developing products and tightly interacting with customers permits SSFs to learn and create new
technical and market knowledge.
Although Beta also interacts with its customers, its management team conceives customers’
relationships as a source of validation rather than a source of new ideas, knowledge creation, and
learning. Beta’s Marketing VP describes it, “our customers are primarily a source of validation as
opposed to innovation.”
4.2 Partners
What emerges from our data is that all five SSFs have a “high” level of interaction with external
partners. Interacting and collaborating with partners has been very important to the success of our sample
firms. Interorganizational collaboration permits firms to learn from each other, exchange information and
knowledge, pool complementary resources, prompt innovation, and share costs and risks. All five SSFs
collaborate frequently and intensely with several partners, both small and large, and national and
international in scope. Alpha’s Marketing VP says, “Working with partners will get you further.” Beta’s
CTO affirms, “There are many partnerships now, especially with software companies from al over the
world.” Gamma’s Business Development VP says, “Partnerships are very important…being able to
work with other firms, basically when you’re a small company, is very important.” Delta’s CEO says,
“We have discussions and we exchange ideas with our partners, like things that are happening in the
industry.” Epsilon’s marketing VP, “There is a lot of knowledge floating around...So when they work
with other partners doing advanced technology in the same field outside, they generate lots of new ideas.”
Overall, our sample firms present a high level of external interaction with customers and partners,
a fact that reveals the significance accorded by SSFs to these relationships. Four out of the five studied
firms have stated that both customers and partners represent a tremendous source of new ideas, new
knowledge, and innovation. Our data suggest that SSFs tend to develop partnerships, whether formal or
informal, in order to share, exchange, and create knowledge and enable organizational learning.
Moreover, interorganizational cooperation provides scale and scope economies that SSFs otherwise
would not have attained. Alpha’s CEO argues that one main advantage of collaborating with network
partners is “that you get to do things that you wouldn’t be able to do by yourself.”
5. IT-Tools
Even though all five SSFs have an intranet in place, they use it for diverse motives and at
different degrees. Alpha and Epsilon exhibit a “high” level of interaction and knowledge creation via
intranet. For these two companies, intranet represents a valuable tool where individual, group, and
organizational knowledge is continuously codified, stored, diffused and renewed. At Alpha and Epsilon,
intranet embodies information and knowledge such as new ideas, innovation processes, technical
solutions, lessons learned during projects, company articles and registered spontaneous conversations
among employees.
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The management teams of these two firms continually encourage their employees to consult,
contribute, and to nurture the content of intranet. Alpha’s Marketing VP says, “When we’re talking about
developing ideas, [intranet] it’s extremely useful because if I’m looking just for new input on ideas, I can
write a short description of what I’m trying to do, the whole company can contribute ideas on how to
solve that problem through different approaches which is really helpful.” Epsilon’s Marketing VP says,
“Someone will go off and do a two-day investigation on something and summarize it and instead of just
sending an e-mail, he’ll post it on the wiki. So this wiki is evolving, and keeping information over time
and also it permits to trigger new ideas.” At Alpha and Epsilon, intranet represents a significant source of
organizational learning and knowledge creation and exchange.
Gamma and Delta present a “medium/low” and “medium/high” level of interaction and
knowledge creation via intranet respectively. At Gamma, intranet is basically utilized by designers and
programmers to safely store and keep software codes. Gamma’s Engineering VP explains, “We don’t use
the wiki as much as we could. A lot of stuff we capture is just thrown in source code [in intranet], and
that’s the intent.” In the case of Delta, as it occurs in Gamma from time to time, intranet is generally used
by employees to store presentations, corporate documents, products’ information, innovation processes,
and products’ manuals. Delta’s Engineering VP relates, “You need a good repository of documents
available for everyone. It’s very important that when documents are produced, presentations are
produced, they’re stored somewhere and they can be easily retrieved by anybody in the corporation.
Formalized documents can provide good guide and sources of ideas. An intranet is very useful for this.”
Although Beta has had intranet since its foundation, the company presents a “low” level of
interaction and knowledge creation via this IT-tool. Beta’s CTO explains that intranet is not integrated
into the daily work of employees. “You know, we don’t spend any particular effort on creating knowledge
management tools, or databases or so on. You have very little, but it’s hard to do so, everything is there
somewhere.” At Beta, knowledge-workers will mainly create knowledge through informal
communication and interaction rather than from IT-tools, states the company’s Marketing VP. “Very
much of it [knowledge] is still in the heads of the various key people. So a lot of it is done verbally.”
Briefly, IT-Tools can be used by SSFs to safely store, diffuse, share, and create knowledge. Cases
such as Alpha, Epsilon, and Delta demonstrate that intranet, for example, enables organizations to
efficiently diffuse exchanges and create knowledge at the individual, group, and organizational levels.
Moreover, intranet can become a valuable repository for safekeeping organizational memory.

Exhibit 3: Knowledge creation processes through interaction in SSFs

Knowledge Creation in SSFs
Interaction
Formal Meetings Informal Communities Project Teams External IT-Tools
Case (CoP / CoS / VC / IN) (Within / Across) (Customers / Partners) (Intranet)

Alpha Level: High Level: Medium (VC) Level: High (“Within”) Level: High (Customers) Level: High

The “corporate Virtual communities (sharing) “Team collaboration “The processes will be along the “When we’re talking
objective meeting creates knowledge lines of how do I listen to my about developing ideas,
represents a place “Most of the articles that we synergies and has a customer, what is the funnel I have [intranet] it’s extremely
that offers fresh publish would be about some multiplier effect on for the customer voice in my useful because if I’m
seeds for new lessons learned or something, knowledge creation” CEO company and what is the innovation looking just for new input
technologies and some new processes that we process for interpreting that on ideas, I can write a
knowledge” have developed or invented, Level: Medium/Low customer voice and transforming it short description of what
Marketing VP that we think that the rest of the (“Across”) into a product” CEO I’m trying to do, the
world should know about, so whole company can
“We sit around in we share past experiences and “Each team can see the “I have to be talking to customers on contribute ideas on how
this room and there learn from each other” CEO processes of others a high level so I come up with new to solve that problem
is a chair person projects at the top, the ideas ” Marketing VP through different
who puts together “We have an intranet site that templates are there, but approaches which is
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