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Management Research NewsVol. 31 No. 11, 2008

pp. 879-894# Emerald Group Publishing Limited

0140-9174DOI 10.1108/01409170810913060

Knowledge creation processes insmall innovative hi-tech firms

Martin Spraggon and Virginia BodolicaDepartment of Management, Marketing and Public Administration, School of

Business and Management, American University of Sharjah, Sharjah,United Arab Emirates

Abstract

Purpose – The purpose of this paper is to explore knowledge creation processes in small innovativehi-tech firms operating in the software industry.Design/methodology/approach – The research framework examines specific action andinteraction processes aiming at creating knowledge. This exploratory research is constituted byfive case studies, each of them being represented by a small Canadian software firm. Analysis drawsupon four sources of data. A total of 15 interviews (three per case) had been conducted andsubsequently transcribed and coded using qualitative software – Nvivo 07.Findings – The results of the study reveal that interaction processes permitting the creation ofknowledge in small hi-tech firms can take place via: formal meetings; informal communities; projectteams; external interaction; and information technology-tools. Rapid prototyping represents thekernel activity of knowledge creation through action. Details of the results, implications of thefindings, and conclusions are presented and discussed.Research limitations/implications – This paper is based on a limited number of case studies,therefore empirical results cannot be generalized. Future research on larger samples of smallCanadian software firms is needed, using the same eligibility criteria and comparing the sameknowledge creation processes as those explored in this study. Other promising avenues of inquiryinclude such questions as the way small knowledge-based firms operating in turbulent environmentsorganize internally to create knowledge, the conditions enabling the generation of knowledge, and theparticular ‘‘spaces’’ in which knowledge creation occurs in these firms.Practical implications – The systematic description and comparison of knowledge creationprocesses in each explored company contribute to the better understanding of specific ‘‘interaction’’and ‘‘action’’ processes through which knowledge is generated, enabling practitioners in smallinnovative hi-tech firms to design appropriate policies and procedures for enhancing knowledgecreation behaviors of their employees.Originality/value – This research is among the first and most exhaustive exploratory andcomparative studies carried out in the Canadian context of small firms operating in the softwareindustry.

Keywords Knowledge management, Knowledge creation, Small enterprises, Computer software,Canada

Paper type Case study

1. IntroductionIn order to survive and remain competitive, small hi-tech firms necessitate creating andrejuvenating knowledge endlessly (Brown and Eisenhardt, 1997; Valkokari andHelander, 2007). Knowledge has become an essential source of value generation andsustainable competitive advantage (Teece, 2005; Nonaka and Takeuchi, 1995). Theability of small hi-tech firms to create knowledge relentlessly and manage itstrategically is viewed as critical to organizational success and survival (Inkpen andDinur, 1998; Nonaka and Teece, 2001; Desouza and Awazu, 2006; Saenz et al., 2007).Firms that develop and leverage knowledge resources achieve greater success thanfirms who are more dependent on tangible resources (Autio et al., 2000). Knowledgemanagement is increasingly becoming an integral business function for many

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companies, as they realize that organizational competitiveness hinges on the effectivemanagement and creation of knowledge (Grover and Davenport, 2001; Randeree, 2006).

Although knowledge creation is viewed by business scholars as fundamental forsecuring a sustainable competitive advantage (Nonaka, 1994; Nonaka and Takeuchi,1995; Prahalad and Hamel, 1990; Teece, 2005) and has become a widespread concernfor firms operating in turbulent and hypercompetitive environments, few studies havesystematically investigated the specific knowledge creation processes put in place bysmall hi-tech firms to generate innovations (Desouza and Awazu, 2006). Understandingknowledge creation processes is critical for small innovative firms in their effort tomake optimum use of both explicit and tacit knowledge flowing within theorganization (Demers, 2003). In order to create value and develop a competitiveadvantage through the innovations’ generation, knowledge must be created andstrategically managed by small innovative firms (Teece, 2005).

In this paper, we focus on analyzing small hi-tech firms through a knowledgemanagement perspective. More specifically, the aim of our research is to further theunderstanding of how and through what processes small firms operating in theCanadian software industry create knowledge to generate innovations. The mainreasons for selecting a Canadian sample of small hi-tech companies are threefold. First,over the last decade this industry’s growth has been the fastest and most important ofthe information and communication technology (ICT) sector in Canada (IndustryCanada, 2006). Whereas, the telecommunication industry’s output since 1997 hasgrown by 86 per cent that of the software and computer services has almost tripled(ICT Statistical Overview, 2006). Second, the software industry represents a vitalsource of employment in Canada, accounting for 240,283 new jobs since 1997, most ofwhich were generated by small software firms (SSFs). Overall, employment in softwareand computer services has increased by almost 90 per cent over the last ten years,compared to 15 per cent in the telecommunications industry (Canadian ICT SectorProfile, 2005). Third, more than 98 per cent of companies operating in the Canadiansoftware industry are small firms composed of less than 100 employees (IndustryCanada, 2006), making this industry even more attractive for the purposes of our study.

Even though the Canadian software industry is considered to be one of the mostimportant ones for enhancing national competitiveness and economic development(OECD, 2004), empirical research is still embryonic in this fast-growing sector.Moreover, the few existing studies carried out on the software industry explored largerather than small firms and have been made more from a technical point of view than aknowledge management perspective (Dayasindhu, 2002; Jacob and Pariat, 2000). It isour belief that knowledge creation processes put in place to stimulate innovations’generation significantly differ in small and large firms and in the software sector thanin other industries. Therefore, we propose in this study a framework that viewsknowledge creation processes as an efficient means for small hi-tech companies to keeppace with technological change, particularly when an innovative firm is seeking tocreate and manage unique and pioneering resources to generate innovations in fast-moving environments.

The next section provides a brief overview of the knowledge managementperspective and its specific knowledge creation processes. We continue by explainingthe research methodology adopted in this study. An in-depth analysis of the cross-casefindings follows. We conclude the paper with a detailed discussion of our results in thelight of extant literature and presentation of avenues for future research.

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2. Literature review2.1 Knowledge management perspectiveA knowledge-based view of the firm is a contemporary approach to strategicmanagement that guides attention toward the understanding of the management of afirm’s core knowledge (Autio et al., 2004; Ling Ku et al., 2005). The extent to whichorganizational knowledge and related organizational learning processes, such asknowledge creation, represent the core elements of innovative firms (Tsoukas andVladimirou, 2001; McEvily and Chakravarthy, 2002; Crossan and Bedrow, 2003; Inkpenand Tsang, 2005). Knowledge has become the most important strategic input andvaluable asset for innovation activities, playing a prominent role in the development ofsmall innovative firms (Nonaka and Teece, 2001; Perez and Sanchez, 2003). Innovationgeneration demands that knowledge be continually renewed and replenished (Brownand Eisenhardt, 1997).

Knowledge is dynamic, relational and based on human action (Davenport andPrusak, 1998; Nonaka, 1994; Nonaka and Takeuchi, 1995). Two types of knowledgeexist, explicit and tacit (Polanyi, 1967; Nonaka and Takeuchi, 1995). Explicitknowledge refers to codified knowledge, which is easily transmitted in a formal,explicit and systematic language. Tacit knowledge refers to knowledge that remainsmuch harder to transfer, formalize or codify, due to its personal quality. Tacitknowledge as opposed to explicit is deeply rooted in action, commitment andinvolvement in a specific situation or context (Nonaka 1994; Tsoukas and Vladimirou,2001) and involves cognitive and technical components.

2.2 Knowledge creationThe creation of new organizational knowledge is increasingly becoming a managerialpriority, particularly for small hi-tech firms operating in fast-moving environments.New knowledge provides the basis for organizational renewal and sustainablecompetitive advantage (Prahalad and Hamel, 1990; Crossan and Berdrow, 2003).Although ideas are formed in the mind of individuals, interactions between individualstypically play a significant role in developing new ideas and creating new knowledge(Nonaka, 1994). Several advocates of the knowledge management perspective conceivean organization as an entity that creates knowledge by virtue of its actions andinteractions with its environment (Nonaka and Teece, 2001; Levinthal and Myatt, 1994).

A ‘‘spiral model’’ of knowledge creation, which explains the continual relationshipsbetween explicit and tacit knowledge has been proposed (Nonaka and Takeuchi, 1995).The interaction between these two types of knowledge is called ‘‘knowledgeconversion’’. Through this ‘‘conversion’’ process, tacit and explicit knowledge increasein terms of quantity and quality (Nonaka and Teece, 2001). There are four types ofknowledge conversion:

. socialization, from tacit to tacit knowledge;

. externalization, from tacit to explicit knowledge;

. combination, from explicit to explicit knowledge; and

. internalization, from explicit to tacit knowledge (Nonaka, 1994).

Effective knowledge creation depends on an enabling context, called ‘‘Ba’’ (Nonaka andTeece, 2001; Saenz et al., 2007). ‘‘Ba’’ is a boundless context shared by those whointeract with each other; through such interactions, participants and context (‘‘ba’’)evolve to create knowledge. ‘‘Ba’’ can possess a physical, virtual and mental dimension.

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Knowledge creation contexts might also be favored by a shared identity (Kogut andZander, 1996), dense social capital (Nahapiet and Ghoshal, 1998) and trust (Das andTeng, 2000).

Knowledge may also be created in the ‘‘spiral’’ that goes through pairs of seeminglyantithetical concepts, such as order and chaos, micro and macro, part and whole, mindand body, tacit and explicit and creativity and control (Nonaka and Teece, 2001). In asimilar vein, successful innovative firms blend limited structure aroundresponsibilities and priorities with extensive communication and design freedom inorder to favor knowledge creation (Brown and Eisenhardt, 1997). This combination isneither so structured that change cannot occur, nor so unstructured that chaosdevelops. This seems to be the case of 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.

3. MethodologyThis exploratory research is constituted by five case studies, each of the casesrepresented by a small Canadian software firm. Due to the complexity and multifaceteddimensions of knowledge, qualitative rather than quantitative analysis is required toexplore knowledge management processes in SSFs. Explorative multiple-case studies(Yin, 2003; Eisenhardt, 1989; Sutton, 1997) constitute the research design with aninductive underlying logic. A case study allows the comprehension of complex socialphenomena because it takes into consideration the contextual conditions that remainextremely pertinent to the phenomenon under investigation (Yin, 2003).

The five cases were chosen in a purposeful fashion (Creswell, 2003) and fortheoretical reasons (Eisenhardt, 1989). The rationale behind purposeful samplingresides in selecting ‘‘information-rich cases’’ that provide an in-depth understanding ofthe phenomena under study (Patton, 2002). The intensity sampling strategy was usedin our research to select information-rich cases that manifest intensely the phenomenaof interest – knowledge creation processes. We expect SSFs involved in innovationgeneration activities to manifest intensely specific knowledge creation processes anddynamics, since knowledge represents their most valuable resource (Heeks, 1999;Torrisi, 1998).

To be eligible for inclusion in the sample, firms needed to meet some pre-establishedrequirements (Table I). In order to avoid selection biases, we decided to retain onlythose SSFs which are perceived as highly innovative by software industry experts. Weconducted informal interviews with 11 industry experts between October 2005 andJanuary 2006. The final sample list was comprised of nine SSFs, all of which werenamed at least twice by different industry experts as those involved in innovationactivities. Six of the nine firms were named at least three times; all of them wereapproached and five accepted to participate in our study. The informal interviews with

Table I.Sample eligibilityrequirements

Sample requirements for eligibility

SSFs Canadian firmSoftware industry�100 EmployeesMain activity: conception, creation, development

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the panel of experts also helped us to gather additional information about the selectedfirms before we approached the firms (Creswell and Symon, 2004).

Our analysis draws upon four sources of data:

(1) in-depth interviews;

(2) public documentation;

(3) archival records; and

(4) direct observation.

In each explored SSF, we gathered information on perspectives from two levels of themanagement hierarchy. The key informants included, among others, the ChiefExecutive Officer (CEO), Chief Technology Officer (CTO), marketing Vice-President(VP), product development VP and project manager. A total of fifteen interviews (threeper case) had been conducted and subsequently transcribed and coded usingqualitative software - Nvivo 07. Interviews typically lasted 90 min, although two ofthem ran as long as 2 h.

To evaluate knowledge creation processes and facilitate comparisons across cases,we created a ‘‘continuous seven-level scale’’ (Brown, 2000). Such a scale allowed us toassign a level to each knowledge creation process along a continuum of seven levels:‘‘low’’; ‘‘low/medium’’; ‘‘medium/low’’; ‘‘medium’’; ‘‘medium/high’’; ‘‘high/medium’’; and‘‘high’’. ‘‘low’’ means that we found (almost) no evidence of a knowledge creationprocess and ‘‘high’’ means that the process occurred in a highly intensive and frequentfashion (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 suchfactors as the intensity, the frequency, and the variance (among cases) of each exploredknowledge creation process by juxtaposing different sources of data (i.e. interviews,observations and internal documents) related to each process (Inkpen and Dinur, 1998).Using qualitative software, we created nodes to help accurately assess the ‘‘density ofcitations’’, and compare patterns, contexts, and knowledge creation processes acrosscases with a high level of accuracy and transparency. Table II describes the firmsincluded in our sample.

4. FindingsWhat emerges from our data is that knowledge creation occurs at the individual,group, organizational and interorganizational levels via two main processes:‘‘interaction’’ and ‘‘action’’. While ‘‘interaction’’ is related to exchange andcommunication, ‘‘action’’ is associated with the execution and implementation ofknowledge.

Table II.Description of sample

SSFs

Firms’ name Nature of technology Founded Total employees

Alpha Web applications 1997 50Beta Security 2004 50Gamma Voice-over-IP 2004 15Delta Wireless mesh system 2001 80Epsilon Network 2003 100

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4.1 Knowledge creation through interactionKnowledge is created by individuals: ‘‘It’ll often start with one developer having anidea or an approach’’, convey all SSFs’ interviewees. Although ideas are formed in theminds of individuals, our data indicate that interactions between individuals, groupsand organizations play a significant role in developing new ideas. We found thatcontinuous communication, exchange and interaction are the keystones of knowledgecreation in all explored SSFs. According to our data, interaction promoting the creationof knowledge in SSFs can take place through: (1) Formal meetings; (2) Informalcommunities (i.e. communities of practice, communities of sharing, virtualcommunities or informal networks); (3) Project teams (i.e. ‘‘within’’ and ‘‘across’’ teams);(4) External interaction (i.e. customers and partners); and (5) information technology(IT)-tools (i.e. intranet).

4.1.1 Formal meetings. All five SSFs have put in place different kinds of formalmeetings for creating and exchanging information and knowledge. Alpha, Beta andGamma, for example, have ‘‘brainstorming sessions’’ which are scheduled in advanceand where all employees are generally invited to participate. The main goal of thesebrainstorming encounters is to bring about new ideas freely, without judging them, inorder to solve specific problems related to an innovation process or a new technology.The management teams from Alpha, Beta and Gamma believe that brainstormingsessions are vital for the generation of new ideas and knowledge.

Delta and Epsilon have developed other kinds of formal meetings to createknowledge. According to Delta’s Engineering VP, the management team has put inplace ‘‘short-intense teaching sessions’’ in order to exchange and create new knowledge‘‘rapidly and intensely.’’ He explains, ‘‘. . .people come up with an idea, they put it onpaper, we get together in a room, and the person that created the idea teaches to the restof the group’’. In the case of Epsilon, Research and Development (R&D) and Marketingemployees have numerous formal reviews with their customers, such as product andspecifications reviews, which permit them to exchange, receive, absorb, and create newknowledge.

4.1.2 Informal communities. According to all five SSFs’ management teams,knowledge creation also occurs via daily informal interaction and spontaneouscommunication and exchange between employees, teams and external partners. Whatemerges from our data is that informal communities and networks are continuouslybeing formed and transformed within and across teams and departments. Based onour analysis and observation, we identified four types of informal communities:communities of practice, communities of sharing, virtual communities and informalnetworks.

Communities of practice are informal and spontaneous communities of people thatshare common interests or goals and gather together in order to solve a given problem.Communities of sharing are formal or informal communities of people that meet toshare and exchange ideas, information and knowledge. Virtual communities are formalor informal communities of people that share common interests, ideas and knowledgeover the internet or other IT-tools. Informal networks refer to informal, voluntary andspontaneous relationships that are developed within an organization among membersand 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 goodexample of informal communities’ formation. In this firm, all employees collaborateand interact closely and intensely in order to provide their inputs to better understand

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and solve a given problem, regardless its nature. From Gamma’s management teampoint of view, knowledge is created ‘‘informally, spontaneously and collaboratively’’ viacommunities of practice and sharing, where all employees participate. According toGamma’s Business Development VP, ‘‘It’ll often start with one developer having an ideaor an approach, and then a solution is sort of fielded by all of us’’. Our data suggest thatextensive informal communities and interaction among employees make it possible tosolve specific problems and create new knowledge and ideas.

At Epsilon communities of practice and sharing are also common phenomena. Theformation of these informal communities are explained by the fact that more than halfof Epsilon’s employees have worked together in the past for other companies and knoweach other quite well. In the case of Beta, most communications are informal andinternal informal networks represent the predominant interaction pattern. Beta’s CTOaffirms, ‘‘The people that have a lot of knowledge, the couple of brains, they areconsulted as need be. It’s informal like that. When you need, you go to see them. It’s justmore of an informal network that way. That’s how we are running now that we aresmall’’. At Alpha, as at Gamma, there are virtual communities of sharing. ‘‘We have anintranet site that lets you publish everything, from a link to an article, and it lets otherpeople either comment on that or even change that article itself’’, explains the CEO.

Overall, our data suggest that informal communication and communities’formation, regardless of their nature, are common phenomena in all five SSFs. Wefound that informal communities enable and prompt individual, group andorganizational learning, knowledge exchange and knowledge creation.

4.1.3 Project teams. Our sample firms are formally structured in flexible and cross-functional project teams aiming at achieving knowledge creation via intense andfrequent complementary resource exchange, communication and interaction.Organizing knowledge-workers into project teams seems to be a common patternacross the five cases. In all explored SSFs, project teams’ participants enjoy a highdegree of empowerment, which permits them to interact, pool resources and takeaction freely within their teams. SSFs’ management teams agree on the extent to whichemployees create knowledge on a daily basis through interaction ‘‘within’’ and ‘‘across’’project teams.

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 worktogether in order to resolve any emerging problem. ‘‘. . .We have fairly good discussionsand just solve the problems all together’’ (Gamma’s Engineering VP); ‘‘. . .we workclosely and we trade information back and forth within and across projects’’ (Gamma’sBusiness Development VP).

Delta has implemented what its employees call ‘‘systems groups’’. These groups areformed by highly specialized programmers, ‘‘market thinkers,’’ and Doctorates inmathematics. At Delta and Epsilon, project teams are considered to be ‘‘permeable,flexible and interchangeable’’ and the resource reallocation across projects is formal,whereas at Gamma it occurs rather spontaneously. In all of these three companies,knowledge is endlessly and freely flowing, being ‘‘re-used’’ and ‘‘re-created’’ viainteraction and new combinations within and across project teams.

Alpha and Beta exhibited a ‘‘medium’’ level of interaction ‘‘across’’ project teams.The former firm tends to keep some limits between teams due to its intellectualproperty policy. Alpha’s CEO explains, ‘‘Each team can see the processes of otherprojects at the top, the templates are there, but the implementation or the filling of thattemplate may have some intellectual property. So we have to keep China walls between

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teams.’’ While at the latter company, teams are ‘‘pushed’’ to collaborate with each otherby the management team because they do not do so spontaneously. According to Beta’sCTO, ‘‘Each function in the company kind of has its own style. Sales people aremanaged on quite a different way than developers are managed’’.

All five SSFs exhibited a ‘‘high’’ level of interaction ‘‘within’’ project teams, whichallowed participants to exchange, acquire, internalize and learn new knowledge andexpand their base of expertise. Interaction ‘‘across’’ project teams enables anorganization to create new knowledge by ‘‘cross-fertilizing’’ knowledge bases from avariety of employees and specialized teams. Our data suggest that previousrelationships among employees may favor both ‘‘within’’ and ‘‘across’’ project teams’interaction. However, interaction ‘‘across’’ project teams is not always natural andspontaneous. Factors such as teams’ cultural differences and organizational valuesmight be an obstacle to knowledge flow and interaction ‘‘across’’ project teams.

4.1.4 External interaction. Since their very conception, Alpha, Gamma, Delta andEpsilon collaborate closely and intensely with their customers throughout theirproduct development projects. These SSFs possess a ‘‘high’’ level of interaction withtheir customers, while Beta exhibits a ‘‘medium’’ level. From Alpha’s Marketing VPstandpoint, ‘‘There’s a huge amount of collaboration that happens with clients’’. Delta’sCEO asserts, ‘‘Customer’s feedback loop is very important. That’s why it is importantto have customers and interact closely with them’’. According to Gamma’s BusinessDevelopment VP, ‘‘You have to get closer to customers. They can be quite useful inlearning about issues that may be affecting the industry’’.

From these four SSFs, customers represent a significant source of inspiration, newideas and innovation. Lead customers, they explain, can reveal new uncharted productneeds that might trigger new technology trajectories. Epsilon’s CEO, for example,affirms that co-developing products and tightly interacting with customers permits SSFsto learn and create new technical and market knowledge. Although Beta also interactswith its customers, its management team conceives customers’ relationships as a sourceof validation rather than a source of new ideas, knowledge creation and learning.

Our sample firms present a ‘‘high’’ level of interaction with external partners.Interacting and collaborating with partners has been very important to the success ofthese SSFs. Interorganizational collaboration permits firms to learn from each other,exchange information and knowledge, pool complementary resources, promptinnovation and share costs and risks. As Gamma’s Business Development VPobserves, ‘‘Partnerships are very important. . . Being able to work with other firms,basically when you’re a small company, is very important’’. Our data suggest that SSFstend to develop partnerships, whether formal or informal, in order to share, exchangeand create knowledge and enable organizational learning. Alpha’s CEO argues that onemain advantage of collaborating with network partners is ‘‘that you get to do thingsthat you wouldn’t be able to do by yourself’’.

4.1.5 IT-tools. Even though all five SSFs have an intranet in place, they use it fordiverse motives and at different degrees. Alpha and Epsilon exhibit a ‘‘high’’ level ofinteraction and knowledge creation via intranet. For these two companies, intranetrepresents a valuable tool where individual, group and organizational knowledge iscontinuously codified, stored, diffused and renewed. The management teams of thesetwo firms continually encourage their employees to consult, contribute and to nurturethe content of intranet, which represents a significant source of organizational learningand knowledge creation.

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Gamma and Delta present a ‘‘medium/low’’ and ‘‘medium/high’’ level of interactionand knowledge creation via intranet, respectively. At Gamma, intranet is basicallyutilized by designers and programmers to safely store and keep software codes. In thecase of Delta, intranet is generally used by employees to store presentations, corporatedocuments, products’ information and innovation processes. Delta’s Engineering VPrelates, ‘‘You need a good repository of documents available for everyone. Formalizeddocuments can provide good guide and sources of ideas. Intranet is very useful for this’’.

Beta presents a ‘‘low’’ level of interaction and knowledge creation via the intranet.‘‘You know, we don’t spend any particular effort on creating knowledge managementtools, or databases or so on’’. In this company, knowledge-workers will createknowledge mainly through informal communication and interaction rather than fromIT-tools. ‘‘Very much of it [knowledge] is still in the heads of the various key people. So,a lot of it is done verbally’’ (Beta’s Marketing VP).

Briefly, IT-tools can be used by SSFs to safely store, diffuse, share and createknowledge. Cases such as Alpha, Epsilon and Delta demonstrate that the intranet, forexample, enables organizations to efficiently diffuse exchanges and create knowledgeat the individual, group and organizational levels. Moreover, the intranet can become avaluable repository for safekeeping organizational memory. Table III summarizes andjuxtaposes our research findings.

Overall, our data suggest that Epsilon exhibits the highest levels of knowledgecreation through interaction, followed by Delta and Alpha. In Alpha’s case, interaction‘‘across’’ project teams aiming at creating knowledge is not very frequent due the firms’internal intellectual property policy. Compared to the rest of the sample, Gammapresents the highest levels of informal communities ‘‘within’’ and ‘‘across’’ projectteams’ and customers’ and partners’ interactions. Beta, as opposed to the other fourSSFs, displays the lowest level of knowledge creation through interaction. Beta’slowest level can be explained by its highly informal and tacit culture that influencesemployees to seldom use intranet as a means of interaction for creating knowledge.

4.2 Knowledge creation through actionKnowledge can be also created by individual or group action. ‘‘Action’’ refers to theimplementation and execution of existing knowledge aiming to create new knowledge.‘‘Learning-by-doing’’ is central to knowledge creation. Rapid prototyping represents aninteresting example of knowledge creation through action or ‘‘learning-by-doing’’.Rapid prototyping is defined as a group of techniques used to quickly fabricate a scalemodel of a part or assembly using three-dimensional computer-aided design. Rapidprototyping permits SSFs to rapidly experiment and test new ideas, reduce theirdevelopment time in a cost-effective fashion, and allows customers to literally‘‘visualize’’ the future product and provide feedback on it.

All five companies do rapid prototyping. However, only Alpha, Beta, Delta andEpsilon possess a rapid prototyping lab and the latter three companies are intensely andfrequently engaged in rapid prototyping activities. ‘‘Good new ideas are prototyped all thetime’’ (Beta’s CTO); ‘‘We try to prototype as soon as possible, even a very small portion ofthe concept, and we do that all the time’’ (Delta’s Engineering VP); ‘‘So we do prototypingto get out new concepts. . . we do countless projects’’ (Epsilon’s Marketing VP).

Alpha and Gamma engage in rapid prototyping activities from time to time orseldom. Alpha has put in place a ‘‘stage gate process’’ though which new ideas arefiltered and funneled. This formal innovation funnel process may explain why only

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Table III.Data summary:knowledge creationprocesses throughinteraction in small hi-tech firms

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very few ideas are prototyped. In the case of Gamma, prototypes are seldom performeddue to its lack of financial resources.

Alpha, Beta and Gamma exhibit a ‘‘medium-high’’ level of customer interactionwhen performing rapid prototyping activities, whereas Delta and Epsilon present a‘‘high’’ level of interaction. According to Epsilon’s CEO, ‘‘The rapid prototyping lab,which we have since we moved into a marketing developing role, is huge for us. Itallows us to really have solid conversations with our customer base’’. SSFs can getimmediate and valuable feedback from their customers when they tightly interact withthem when performing rapid prototyping activities. Customers are considered to be asignificant source of new ideas and innovation.

For our sample firms, the rapid prototyping lab represents an important source ofknowledge creation via experimentation and exploration. Beta, Delta and Epsilon exhibita ‘‘high’’ level of exploration and experimentation when involving in rapid prototypingactivities, while Alpha and Gamma present a ‘‘medium-high’’ level. ‘‘They’ve [employees]got some idea they want to explore, let them have time to explore it. Let themexperiment’’ (Beta’s CTO). In fact, Beta enjoys strong financial support from its venturecapitalist partners, allowing it to engage fairly often in both exploration andexperimentation, and radical innovation generation. Alpha and Gamma prefer to focusjust on exploitation activities and less radical innovation creation.

Rapid prototyping also permits SSFs to engage in ‘‘trial-and-error’’ activities,carrying out regular planned operations, observing outcomes and then revising futureaction. All sample firms show a ‘‘high’’ level of ‘‘trial-and-error’’ activities whenperforming rapid prototyping, since they imply less risk and lower technological,market, organizational and resources’ uncertainties.

At Alpha, Gamma, Delta and Epsilon R&D and Marketing employees collaborateclosely in order to test existing ideas and explore and experiment unchartedtechnologies and new ideas emanating from both internal and external sources. TheseSSFs believe that interaction and iterations between R&D, Marketing, and customersare extremely fruitful generating new knowledge. As Epsilon’s Marketing VP states,‘‘. . . the rapid prototyping lab actually reports into marketing. . . that really helped tobecome more experimental’’. Gamma does not have a rapid prototyping lab. Due to itssmall size and scarce resources, this SSF tends to rationalize and focus its innovationefforts to respond to specific clients’ demands.

What emerges from our data is that rapid prototyping activities permit SSFs tocreate new knowledge by exploring, experimenting, developing and testing new ideasand concepts. Close and intense interaction with customers during rapid prototypingactivities appears to be extremely important for SSFs. Delta and Epsilon exhibit ‘‘high’’levels of customer interaction when performing rapid prototyping activities, followedby Alpha, Beta and Gamma which display a ‘‘medium/high’’ level. This result might beexplained by the fact that larger firms, such as Epsilon and Delta, tend to deal withlarger customers that need to collaborate more intensely throughout the innovationprocess in order to reduce technological and needs’ uncertainties. Management teamsin all the case SSFs believe customers can provide lots of information, new ideas andknowledge to enable and prompt innovation.

We also found that larger firms (in terms of the number of employees) experiment,explore, and test new ideas, technologies and concepts much more frequently thansmaller ones. This higher frequency in larger companies, such as Epsilon and Delta,can be explained by the fact that they possess more financial and human resourcesthan smaller ones. Table IV synthesizes and compares our findings.

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5. DiscussionAs argued by Nonaka and Teece (2001), we found that SSFs create knowledge byvirtue of their actions and interactions. According to our results, interaction allowingthe creation of knowledge in SSFs can take place via: (1) Formal meetings; (2) Informalcommunities; (3) Project teams; (4) External interaction; and (5) IT-Tools. Our data arein line with Grant’s (1996) and Nonaka and Takeuchi’s (1995) findings, which suggestthat knowledge is created by individuals. Although ideas are formed in the minds ofindividuals, interactions among people typically play a significant role in developingnew ideas, as evidenced in all explored SSFs.

Knowledge creating interaction through formal meetings, informal communities,project teams and external interaction generally takes place through ‘‘socialization.’’Nonaka and Takeuchi (1995) affirm that ‘‘socialization’’, a process through which tacitknowledge and experiences are shared, enables the generation of new knowledge. VonHippel (1988) stresses the importance of developing tight interactions with customersto get new ideas. Even though our results support the findings of these researchers, wealso argue that ‘‘intense teaching sessions’’ and ‘‘communities of practice’’ are processesthrough which employees share tacit knowledge and create new knowledge.

Similar to Nonaka and Takeuchi (1995), we found that knowledge creation throughIT-tools, another interaction process, occurs via ‘‘externalization’’ and ‘‘combination’’.However, in our study, we go beyond existing evidence, observing that knowledgecreation using IT-tools can also take place via what we call ‘‘virtual-socialization’’.Virtual-socialization is a process through which individuals or groups interact usingdiverse IT-tools. Virtual communities of interaction appeared to be a frequent andformal knowledge creation practice in two SSFs we explored. This finding differs fromNunes et al. (2006), who state that ‘‘knowledge management activities withinknowledge-based small medium enterprises tend to happen in an informal way andrarely supported by purposely designed ICT systems’’. Contrary to Nunes et al. (2006),we show that some SSFs, such as Alpha and Epsilon, not only implemented knowledgemanagement processes exhibiting ‘‘high’’ levels of formalization, but also purposelydesigned some IT-tools (i.e. ‘‘knowledge libraries’’) to create knowledge.

Knowledge can also be generated by individual or group action. We found thatsome SSFs prefer to create knowledge principally through ‘‘learning-by-interacting’’(i.e. Gamma), while others prefer ‘‘learning-by-doing’’ (i.e. Beta). We focused on ‘‘rapidprototyping’’ activities in SSFs to investigate knowledge creation through action.Rapid prototyping allows firms to exchange market and technological knowledgewith customers and, as a result, create new knowledge. Again, this finding stronglysupports Von Hippel’s (1988) results regarding the role of external players

Table IV.Data summary:knowledge creationprocesses through actionin small hi-tech firms

Action: rapid prototyping

Case Lab Frequency Customers’ interactionExploration/experimentation Trial-and-error

Alpha Yes From timeto time/often

Medium/high Medium/high High

Beta Yes Often Medium/high High HighGamma No From time

to timeMedium/high Medium/high High

Delta Yes Often High High HighEpsilon Yes Often High High High

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(i.e. customers) as significant sources of new ideas and knowledge. Moreover, weidentified three specific knowledge generation practices – experimentation,exploration and trial-and-error – that can be performed separately or jointly by SSFsengaged in rapid prototyping activities.

In the case of experimental practices, knowledge-workers deploy controlledsituations and variables in order to create systematic experiences and new knowledge.This finding strengthens Cook and Campbell’s (1979) and Miner et al.’s (2001) results.According to their results, organizations deliberately vary activities and conditions viaexperimental learning to create new knowledge. In contrast to experimentation,exploration activities can be defined as ones in which knowledge-workers attempt todiscover something new, have no control over the situation, and have no a priori,predefined plan of action. March (1991) associates exploration with behaviors such asresearch, discovery, and incurring into new courses of action. Going a step further, wesuggest that exploration practices are likely to be performed by firms engaged intechnology-oriented rather than market-oriented activities, and that they tend totolerate higher levels of technological and market uncertainties.

‘‘Trial-and-error’’ processes refer to those through which a firm repeats activitiesthat appear to produce successful outcomes and avoids those that appear to bedisappointing (Cheng and Van de Ven, 1996). In this study, we not only corroborateMiner et al.’s (2001) results, finding that ‘‘trial-and-error’’ activities permit firms tocreate knowledge involving in lower levels of risk but also provide additional evidencethat ‘‘trial-and-errors’’ are likely to be performed by those SSFs that are more market-oriented and exhibit a higher level of process formalization.

6. ConclusionNonaka and Teece (2001) and Levinthal and Myatt (1994) conceive an organization asan entity that creates knowledge though actions and interactions with its environment.Confirming the results of these authors, we attempt in this study to go a step further byexploring the particular ways through which interactions and actions enable a SSF tocreate knowledge to generate innovations. To our knowledge, this investigation isamong the first and most exhaustive comparative studies carried out in the Canadiancontext of small firms operating in the software industry. The systematic descriptionand comparison of knowledge creation processes in each explored company contributeto the better understanding of specific interaction and action processes through whichknowledge is generated, enabling practitioners in small innovative hi-tech firms todesign appropriate policies and procedures for enhancing knowledge creationbehaviors of their employees.

Despite these contributions, our research presents some limitations. Given that ouranalysis and insights are based on only five case studies, we can not be completely sureabout the degree of external validity or generalization. Nevertheless, in order toimprove the external validity of our study, we invited a panel of eleven industryexperts to make a list of SSFs they consider to be highly innovative. By setting up apanel of experts and approaching the most named companies, we believe our sample ishighly representative of the population under investigation. In addition, theoretical oranalytical generalizations are possible if the same ‘‘behavioral patterns’’ are foundacross cases. Since only five SSFs were included in the sample, results could possiblypredict that specific organizational behaviors in a given context favor breakthroughinnovation generation.

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Another limitation is related to the fact that we have gathered information on theperspectives of such SSFs’ key informants as CEOs, VPs and project managers. Theemployees working in these SSFs were not available and did not have the time toformally participate in this study. During our onsite visits, however, we succeeded ininvolving in some informal exchanges of ideas and perceptions with employees and wetook that information into consideration during the analysis phase.

It is our belief that it is necessary to continue exploring knowledge managementprocesses and dynamics in the particular context of small knowledge-based firms. Forinstance, the limitations of this study raise the need to validate and refine our findingsregarding the way small hi-tech firms create knowledge. Future research on largersamples of small Canadian software firms is needed, using the same eligibility criteriaand comparing the same knowledge creation processes as those explored in ourinvestigation. Other promising avenues of inquiry include such questions as the waysmall knowledge-based firms operating in turbulent environments organize internallyto create knowledge, the conditions enabling the generation of knowledge and theparticular ‘‘spaces’’ or ‘‘ba’’ in which knowledge creation occurs in these firms.

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About the authorsMartin Spraggon is an Assistant Professor of Strategy and Management at the AmericanUniversity of Sharjah (UAE). He holds a PhD from the HEC–Montreal (Canada), DESS from theESC–Paris, MBA from the Sherbrooke University (Canada) and License in Psychology from theUCA (Argentina). He has a considerable international experience, having held positions inbusiness as a Marketing Director, working as a Consultant in the high-tech industry for a broadrange of organizations, and teaching in several universities in North America, Western Europeand Latin America. He conducts research in the fields of knowledge management, innovationmanagement and international business. Martin Spraggon is the corresponding author and canbe contacted at: martin.spraggon-hernandez@hec.ca

Virginia Bodolica is an Assistant Professor at the American University of Sharjah (UAE)where she teaches general management and strategic business policy courses. With a PhDearned from the HEC–Montreal (Canada), MBA from the University of Nantes (France), DESSfrom the IFAG Sofia (Bulgaria), MA from the College of Europe (Poland/Belgium) and BBA fromthe AES Chisinau (Moldova), she has a significant international experience living, teaching andconsulting in different countries around the globe. Her main research interests are related tostrategic management in knowledge-based companies, corporate governance, compensationpractices for strategic employees and cross-cultural management.

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