mindful deviation through combining causation and...

Mindful Deviation throughCombining Causation andEffectuation: A DesignTheory-Based Study ofTechnology Entrepreneurship

Marine Agogué, Mats Lundqvist andKaren Williams Middleton

Technology entrepreneurship can be seen as building upon, while also deviating from, tech-nological paths. Such deviation has primarily been described as singular events where indi-viduals with prior knowledge discover a new opportunity. In this article, we will instead studydeviation as a process of collective decision making, seen more as something mindful thansingular. The purpose is to explore mindful deviation as decision making by nascent technol-ogy entrepreneurs as they conceptualize an early platform technology. Based on case assign-ments undertaken by 13 teams in a venture creation programme, C-K design theory is used totrace how nascent technology entrepreneurs in action combine causal and effectual decision-making logics. Individually answered questionnaires also offered insights into how the entre-preneurs perceived their decision making in hindsight. The findings break with our receivedwisdom around how opportunities are recognized as well as how effectual and causal logicsoccur. As a result, mindful deviation through combinations of effectual and causal logic issuggested as a means to understand early-stage technology entrepreneurship.

Introduction

Understanding how to draw from, but alsodeviate from, the larger technological

setting is central in technology entrepreneur-ship (Shane & Venkataraman, 2003; Bailetti,2012; Garud, Gehman & Giuliani, 2014;Ratinho, Harms & Walsh, 2015). Technologyentrepreneurship is therefore seen as moredependent upon technological paths com-pared to entrepreneurship in general (Garud& Karnøe, 2003). Technology entrepreneur-ship is also associated with more deviatingand path-breaking behaviour when comparedto technological innovation in general (Garud& Karnøe, 2001b). In the path dependency lit-erature, deviation is mostly depicted as a dis-crete or abrupt event, for example a singularevent of discovery (Sydow, Schreyögg & Koch,

2009). The concept of mindful deviation(Garud & Karnøe, 2001b) opens up for a per-spective in which articulated decision making,rather than singular accidental events,explains how path breaking occurs. However,the field currently lacks means to effectivelytrace and interpret early entrepreneurialdecision-making processes that lead to pathbreaking.

In this article, we investigate technologyentrepreneurship as mindful deviation fromtechnological paths. Nascent technology entre-preneurs are asked to graphically illustratetheir conceptualization of a technology plat-form using a design theory called C-K theory.The diagrams are interpreted as indicating theoccurrence of causal and effectual decisionmaking (Sarasvathy, 2001), as are also theresults from a questionnaire measuring

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perceived use of these logics in hindsight bythe entrepreneurs.

C-K theory offers a graphical representationof design activities through diagrams(Hatchuel, Le Masson & Weil, 2004; Agoguéet al., 2014). These diagrams include the twospaces, concept-space (hereafter C-space) andknowledge-space (hereafter K-space), andillustrate the gradual expansion of these spacesas well as how new concept attributes some-times stimulate the search for new knowledgeand vice versa. K-space emphasizes things weknow are identifiable as true or false and seenas readily accessible, such as knowledge mani-fested in patents. C-space represent concepts,which cannot be identified as either true orfalse, but are more or less desirable, such as an‘intelligent car’. A C-K diagram is thus a toolthat can be used to represent an early designprocess in which attributes for a futureproduct are determined (see Figure 1). In thisstudy, C-K diagrams are interpreted intooccurrence of causal or effectual decisionmaking based upon a generated framework.

Effectuation has been identified as adecision-making logic used by experiencedentrepreneurs during situations of uncertainty,in collaboration with committed stakeholders(Read & Sarasvathy, 2005; Sarasvathy, 2008;Dew et al., 2009). Effectuation enables entre-preneurs to co-create new and unanticipatedeffects from known means (Read & Sarasvathy,

2005; Wiltbank et al., 2006; Sarasvathy, 2008),and is a complementary alternative to causa-tion. Causation involves processes used toselect and/or predict actions towards specifi-cally set goals – a predictive, and thusmore consequential, decision-making logic(Sarasvathy, 2001).

Causal and effectual decision making havemainly been explored conceptually or empiri-cally in hindsight (Perry, Chandler & Markova,2011). Therefore, we know less about theactual causal- and effectual-based behaviour ofentrepreneurs (Sarasvathy & Venkataraman,2011; Fisher, 2012; Nielsen & Lassen, 2012).This motivates an explorative use of C-Ktheory to detect such decision making in realtime. Furthermore, by also measuring in hind-sight perceptions of decision-making logicsregarding to the same situation, comparison toprevious studies can be made (Chandler et al.,2011; Perry, Chandler & Markova, 2011). Takentogether, the purpose of this article is toexplore mindful deviation in technologyentrepreneurship as decision making combin-ing effectual and causal logics, using bothreal-time (C-K diagrams) and hindsight (ques-tionnaire) methods.

The article is structured as follows. First ofall, we propose an analytical framework fortracing conscious entrepreneurial decisionmaking based on causal and effectual logicsthrough application of C-K theory (Hatchuel &

Figure 1. Principles of C-K Theory Displayed in a C-K Diagram

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Weil, 2009). We show that the different princi-ples of causation and effectuation can bederived from steps illustrated through C-Kdiagrams. We apply the framework to a studyof 13 teams of nascent technology entrepre-neurs in a venture creation programme (VanBurg et al., 2008; Lackéus & WilliamsMiddleton, 2015) as they are asked to explore(and add to) a patented technology platform.The discussion focuses on how the findingsbreak with existing understandings of oppor-tunity recognition, as well as how effectualand causal logics occur. Finally, limitations ofthe current study and future research needsare discussed.

Literature Review

To explore decision making as a way of under-standing deviation and path breaking in tech-nology entrepreneurship, we review literatureaddressing mindful deviation. We go on tolink this literature to developments aroundentrepreneurial decision making through cau-sation and effectuation. Finally C-K diagramsare introduced as well as how such diagramscan be interpreted to identify occurrence ofcausal and effectual logics.

Mindful Deviation inTechnology Entrepreneurship

Recent research has investigated processesleading to the creation of new opportunitiesthat deviate from established technologicalpaths (Marvel & Lumpkin, 2007; Doganova &Eyquem-Renault, 2009; Beckman et al., 2012).Such processes tend to be studied from a socialperspective: for instance, Doganova andEyquem-Renault (2009) explore how technol-ogy entrepreneurs use business models asdevices to interact with potential stakeholdersand explore different market opportunities.Focusing on reasoning processes, Marvel andLumpkin (2007) describe the cognitive mecha-nisms technology entrepreneurs mobilize toshape innovation radicalness. This is done bystressing the role of different types of knowl-edge in the construction of radical innovation.A challenge for the technology entrepreneuris to draw from technological paths whilealso becoming path-breaking and deviatingtowards new opportunities. The current domi-nant view is that entrepreneurial opportu-nities stem from discovery rather than fromdeliberate processes (Shane & Venkataraman,2000). Such essentially ‘singular’ events of dis-covery have been related to persons eitherwith more prior knowledge in an area (Shane,2000) or having strong pattern-recognitioncapabilities (Baron, 2006).

Mindful deviation has been defined as tech-nology entrepreneurs articulating and creatingrelevance around opportunities that are pathbreaking (Garud & Karnøe, 2001b, 2003). Inemphasizing articulation and relevance, it ispossible to relate the concept to a collectivedecision making involving others to be onboard or at least convinced about a deviation.Mindful deviation, to our knowledge, has notbeen used to empirically study initial identifi-cation of a new concept or opportunity. Ifmindfulness, in terms of articulated decisionmaking, could be conceptualized and empiri-cally traced, then early-stage path-breakingbehaviours could be demystified, be mademore manageable, and be seen as less associ-ated with individual creativity or capabilitiesonly. Before introducing a means for tracingearly-stage decision making, we first needtheory to address decision making.

Principles of Causation and Effectuation

The two decision-making logics of effectuationand causation can help us understand theprocess of mindful deviation. We have alreadyintroduced causation as a commonly appliedlogic in which a course of action is basedupon a predetermined goal, including themarshalling of resources to achieve that goal(Sarasvathy, 2001, 2008). Causation operates ona set of principles: set a goal and focus on whatought to be done to achieve that goal, pursuethe best opportunities towards achieving thegoal, surprises or deviations from the goalshould be prevented whenever possible, setup contractual relationships that facilitateachieving the goal, and predict the future inorder to control it. Causation is seen as a viabledecision-making logic under known or know-able conditions (Sarasvathy, 2001).

Effectuation is the logic utilized to makedecisions based on readily available means,rather than on predetermined goals(Sarasvathy, 2001, 2008). Effectuation arguesthat (expert) entrepreneurs develop adecision-making capacity that allows them toexplore new opportunities jointly with com-mitted stakeholders, particularly in situationsof uncertainty or unknowable future conse-quences. Researchers claim that (expert) entre-preneurs use their available means to developopportunities based on guesses about uncer-tain future preferences (Sarasvathy, 2001, 2008;Read & Sarasvathy, 2005; Sarasvathy & Dew,2005; Dew et al., 2009; Read et al., 2011). Thus,effectual decision making is seen as moreviable than other decision-making logics whenoperating in uncertain and unpredictable cir-cumstances, because it emphasizes the entr-epreneur’s own action as the basis for controland progress (Sarasvathy & Dew, 2005).



Effectuation is proposed as an alternativeand complementary approach (not a replace-ment) to causation (Sarasvathy, 2001;Sarasvathy et al., 2008; Chandler et al., 2011).Thus, mirroring causation, effectuation alsobuilds upon five core principles: start with agiven set of means focusing on what can bedone, risk no more than you can afford to lose,leverage contingencies, form alliances withcommitted stakeholders, and focus on thethings you can control to shape the future whenit is seen as unpredictable (Sarasvathy, 2008;Read et al., 2011). The principles of causationand effectuation are summarized in Table 1.

Just as mindful deviation emphasizeshuman actions of articulation and relevance,effectuation also positions human action

centrally but as the ‘predominant factorshaping the future’ (Sarasvathy, 2008, p. 87).However, methods to detect effectual logic inaction remains underdeveloped (Obrecht,2011; Fisher, 2012). Causation requires one tomake sense of a linear process of aligningresources towards a pre-defined goal. Detect-ing effectuation implies highlighting theexpansiveness of the process, i.e. the possibledifferent paths that entrepreneurs explore(Sarasvathy, 2003; Sarasvathy et al., 2008). Oneway to model decision making is to modelthe diversity of the explorative activities thatan entrepreneur undertakes. These activitieswould include the conceptual ideas an entre-preneur explores but chooses not to buildupon, the knowledge an entrepreneur both

Table 1. Interpretation of Causation and Effectuation in C-K Theory Framework

Description Interpretation in C-K theoryframework

Causalprinciples

Focus on optimal scenarios andreaching pre-set goals

Start with given goals

Make explicit the use of yourknowledge base

Calculate upside potential andpursue the best opportunity

Explore one linear path and evaluateodds

Set up transactional relationshipswith customers and suppliers

Focusing on the existing paths thatyou are not currently operating in

Prevent as much as possible negativecontingencies or unexpectedevents that affect the desired goal

No new disruptive concepts(avoiding introduction ofexpansion in the C-space)

The future can be readily predicted Control and anticipation of allknown possibilities (extensive Kmapping)

Effectualprinciples

Focus on doing the doable andpushing it forward

Start with given means: who you are,what you know and who youknow

Making explicit both the knowledgebase and the conceptual paths atyour disposal

Calculate downside potential, andrisk no more than you can affordto lose

Evaluating multiple paths, as well asthe ability to shift from one path toanother (understanding the linkbetween C and K)

Build your market together withtrusted critical stakeholders

Expanding in both C and K toexplore all possible paths,regardless of existence

Any contingency (even negative) cantrigger imaginative rethinking ofpossibilities and transformation oftargets

Explore all alternatives, includingdisruptive concepts

Using strategies for creating a future Achieving robustness, allowing forfuture possible alternatives



starts with and acquires, and the resources anentrepreneur mobilizes in his/her network ofstakeholders. These actions of entrepreneurscan be seen as a design process. This is whyC-K design theory is used here to detect occur-rence of decision making.

C-K Theory

C-K theory is a theory of design, based onempirical studies of more or less radical devel-opment of technology-based products (Hooge,Agogué & Gillier, 2012; Hatchuel, Weil & LeMasson, 2013). In C-K theory, design is definedas the process of generating new things(Hatchuel, Weil & Le Masson, 2013;Chakrabarti & Blessing, 2014), and involvesboth a specific mode of reasoning (Simon,1996), and a collective process that enables indi-viduals and/or organizations to propose inno-vative products or services, and new businessmodels or strategies (Hatchuel, Le Masson &Weil, 2005). C-K theory relies on modellingexpansion, understood as the extension ofexisting definitions of objects in diverse direc-tions (Hatchuel & Weil, 2009) with the objectiveto both explore and substantiate new ideas.Among the diverse theoretical frameworksproposed in the field of design, C-K theory(Hatchuel & Weil, 2009) holds specific proper-ties (Sharif Ullah, Rashid & Tamaki, 2012) thatcan be of particular interest towards furtherunderstanding of causation and effectuation.

C-K theory establishes distinction betweentwo spaces: a space of knowledge (K-space),defined as a set of propositions that all have alogical status and thus are recognized as eithertrue or false; and a space of concepts (C-space)defined as a set of undecidable propositions –propositions that have no logical status andthus cannot be proven as either true or false.The K-space maps all the knowledge necessaryto understand and develop an idea into action.The C-space is a tree-structure of undecidablepropositions, where each node of the tree cor-responds to a partition (in the mathematicalsense) of the mother concept into severalsub-concepts (see Figure 1). Thus, the C-spacemaps explorable alternatives, but alternativeswhich require new knowledge in order to beput into action. C-K theory links the explora-tion of different alternatives (labelled as ‘con-cepts’ and positioned in the C-space) to theresources required to address and developthese potential ideas by mapping the knowl-edge associated to each alternative in theK-space. Through this modelling process, C-Ktheory can illustrate application of differenttypes of decision making. Mapping in theC-space allows for discussion associatedto effectual logic, where means (existingknowledge/resources) are used to explore

and expand on new concepts. The conver-gence on a particular goal, use of causal logic,is done by bringing together different sets ofknowledge, modelled as a single path in theC-space with the knowledge associated to eachattribute that constitutes the idea at the core ofthe design process. C-K theory allows for par-allel exploration of several ideas as differentpaths in the C-space, as well as surprising dis-covery of new areas of knowledge.

Graphical representation of design activitiesis possible through a C-K theory-based toolcalled a C-K diagram (Agogué et al., 2014). AC-K diagram illustratively maps the C-spaceand the K-space, representing the modellingexpansion of these two spaces, and distinctionof differentiating alternatives. It is thereforea tool that can be used to model a designprocess, including the status, at a precise time,of the available knowledge and various attrib-utes added to the initial concept during thedesign process. A C-K diagram can be appliedin different ways, but it is particularly useful inallowing representations of a design processand thus support an enriched discussion withother actors (for an extensive list of applica-tions, see, e.g., Hooge, Agogué & Gillier, 2012).C-K theory is unique in that it has focused onspecific design processes that lead to disrup-tive ideas (for an extensive literature reviewon C-K theory, see Agogué & Kazakçi, 2014).Thus, a C-K diagram can be seen as a usefuland unique tool for studying mindful devia-tion in early-stage idea development, as itaccounts for diverse paths of exploration andthe associated necessary learning, throughknowledge acquisition, in order to make con-cepts actionable. Moreover, by using a C-Kdiagram, an individual or a group can gener-ate discussions covering several dimensions:what knowledge or attributes have been deep-ened, what are the alternatives that have beendiscussed and/or chosen, what design pathsremain unexplored and, eventually, whichpath to pursue (Agogué et al., 2014).

Using C-K Diagrams to DetectCausation/Effectuation:An Analytical Framework

Building on mindful deviation, causation/effectuation and C-K theory, we propose ananalytical framework to trace causal and effec-tual decision making using C-K diagrams(summarized in Table 1), in a vein similar toprevious work matching causation and effec-tuation to R&D context dimensions (see, e.g.,Brettel et al., 2012, p. 169).

In Table 1, causation, in general terms,involves the development of optimalscenarios and reaching preset goals. This can



be interpreted as determining a defined goalfor the development of an idea, and thenexplicitly identifying the knowledge requiredto reach that goal, including identifying howto obtain the knowledge required. Knowledgeidentification emphasizes validating what isknown because the outcome should be pre-dictable. Anticipating expected returns (thirdrow in Table 1) equates to exploring one linearpath (alternative) in the C-space, identifyingthe knowledge associated to this alternative inthe K-space, and evaluating the value and theassociated risks of this single path. In thissense, a causal process would appear as asingle path in the C-space that stimulates thegathering of relevant pieces of knowledge,such as potential economic gains or strategiesto face potential risks.

The focus on the competitive landscapeinvolved in the causal decision making (fourthrow in Table 1) can be seen as focusing on thepaths that already exist and that are currentlyexplored by different stakeholders. Exploita-tion of these existing known paths triggerspositioning of the chosen path in a more stra-tegic way, stressing the similarities and differ-ences between the chosen path and pathsexplored by competitors, with the aim ofgaining competitive advantage. Avoidingenvironmental contingencies means avoidingsurprises, such as the emergence of disruptiveconcepts (fifth row in Table 1). A C-K diagramof a causal decision-making process would notdisplay new surprising paths in the C-space, orexpansion in the knowledge space. Finally, thepredictive principle in a causal logic refers tothe control and anticipation of all known pos-sibilities, requiring an extensive mapping ofthe K-space with much overlap between thecombined pieces of knowledge, in order toconsider the decision-making process as aclosed one, where all the possible events areanticipated.

The effectuation principles are presented inrows seven through eleven in Table 1. The firstprinciple states that one should start with theset of means readily available, which in a C-Kdiagram involves explicitly mapping the exist-ing knowledge around the initial idea. A C-Kdiagram including effectuation develops in theC-space to display multiple partitions leadingto several alternative paths which are achiev-able based upon collected knowledge, withoutpredetermining which path should be selectedas the outcome of the process.

Focusing on affordable loss (row eight inTable 1) can be seen as evaluating multiplepaths, as well as the ability to shift from onepath to another. In a C-K diagram this is illus-trated through links between the C-space andthe K-space when one path appears as a dead

end. Referencing back to the knowledge andexpertise associated with the dead-end pathcan allow for identifying new value foranother partition (new pathway). The first twoeffectuation principles underline possiblegains from experimenting with as many strat-egies as possible within the given limitedmeans available (Read et al., 2011).

Strategic alliances (row nine in Table 1) canbe traced through expansion in both theC-space and the K-space relative to thecompetencies and resources of associatedstakeholders, including interpretation of valuepropositions not only for the entrepreneurhim/herself, but also for the network of stake-holders. This increases value options acrossthe network of actors, and grants robustnessto the design process of the entrepreneur.Leveraging the environmental contingencies(row ten in Table 1) can be understood asexploring but also exploiting surprises in theC-space. Typically, unexpected disruptiveconcepts that challenge existing representa-tions of the given problem are appreciated(rather than problematic), as they are seen asopportunities to explore further unpredictedvalue. Reaction to this unpredictability,through application of C-K theory, addressesbuilding alternatives that are able to accom-modate variations of context. As a result, suchalternatives can be seen to be adaptablewithin a dynamic environment, and thus arenot predetermined based on a need to executeplanning.

The framework to identify use of causal andeffectual decision making through C-K dia-grams is exemplified in Figure 2 and 3.Figure 2 illustrates how path trajectories builtmainly on use of causal logic would appear ina C-K diagram. Existent knowledge is used toestablish a concept in the C-space which is tofollow a predetermined goal. The singular par-tition and expansion shows development ofthe concept along the predetermined path.New knowledge to be acquired in the K-spaceis based upon the set goal.

Figure 3 shows how a C-K diagram maylook if effectual logic is utilized while devel-oping a new idea. The existing knowledge inthe K-space is used to develop a concept thathas multiple partitions. Some partitions aremore obvious while others are more surpris-ing, but all generate the need to determinenew knowledge in the K-space. The newknowledge may be expansion of the initialexisting knowledge, or it may be knowledgeor resources associated to stakeholders. Thefinal path for development of the idea is notpredetermined, but rather emerges from theoptions generated through linking the C and Kspaces.



Method and Material

Nascent Technology Entrepreneurs atChalmers University of Technology

Our present study is based on the analysis of13 teams of nascent technology entrepreneursduring their first year at Chalmers School ofEntrepreneurship (Gothenburg, Sweden).As the programme is based at a technical uni-versity, the majority of nascent technologyentrepreneurs have a background in engineer-ing or bioscience, with the remainder havingexpertise in business, law, economics, etc.(Lundqvist & Williams-Middleton, 2008). Thetwo-year international master of scienceprogramme at Chalmers School of Entrepre-neurship mainly attracts individuals who aimto have entrepreneurial careers in technology-or bioscience-based start-up firms, or alterna-tively in established technology-basedorganizations. The program is action-based(Rasmussen & Sørheim, 2006), emphasizinglearning-by-doing (Cope & Watts, 2000), withmore than half of the participants entering intoa venture creation approach (Ollila & Williams

Middleton, 2011). This approach requiresparticipants to directly engage in bringingto market technology transfer inventions(Lackéus & Williams Middleton, 2015)through a nine-month incubation period in thefinal year of the two-year-long programme.We argue that participants attending theprogramme are nascent technology entrepre-neurs, having entrepreneurial intention (par-ticularly those who will enter the venturecreation in the second year) based on theirapplication and admission to the programme.They are also well trained in the use of scien-tific methodology and engineering science,based on their previous education. Histori-cally, 15–20 per cent of the participants con-tinue as entrepreneurs in the technologyventures initiated through the programme(Williams Middleton & Donnellon, 2014). Avast majority of the graduates engage profes-sionally in technology-based business devel-opment at start-ups or in established firms(Berggren et al., 2010; Lundqvist, 2014).

After being given instruction in innovativedesign theory, 60 nascent technology entrepre-neurs, grouped into 13 teams, were given four

Figure 2. Causation through C-K Theory

Figure 3. Effectuation through C-K Theory



days to apply C-K theory and make C-K dia-grams around a technology platform. Theywere first introduced to C-K theory and theC-K diagram methodology, both conceptuallyand through a basic example, in a lectureformat supported by complementary readingmaterial. They then worked in their teams overthe four days and interacted with an instructorwho provided feedback and support. Eachteam was asked to produce a C-K diagram.C-K theory and C-K diagrams were notcommunicated in relation to either mindfuldeviation, or decision-making logics; nor werethe nascent technology entrepreneurs pro-vided specific training in mindful deviationor decision-making logics (causation andeffectuation).

C-K theory was applied to a real-life butshelved innovation called Samba Sensor(Figure 4 provides an example C-K diagramcreated by one of the teams). The basic tech-nology behind Samba Sensor is a pressuresensor in which fibre optics allow for pressuremeasurement, applicable to a variety of inter-esting areas: for example, monitoring heartsand other body organs, measuring car com-bustion, or measuring difficult-to-access pro-duction environments, such as oil extractionand telecom monitoring. Samba Sensor can bedescribed as a technology platform consistingof eight patents covering basic functions of thesensor as well as different areas of use.

Prior to introduction of C-K theory, the 13teams had assessed the feasibility of theSamba Sensor innovation. To complete this, theteams were required to delve into the specificsof the patents and make initial choices regard-ing value and utility of the technology plat-form. While none of the nascent technologyentrepreneurs had previous experience withinthe particular innovation area, the assessmentprovided a baseline knowledge of the technol-ogy that facilitated exploring possible futureopportunities based (to some extent) upon thegiven technology platform when applying theC-K theory. For 11 of the 13 teams, C-K theorywas utilized for developing product conceptsand new applications. For the remaining twoteams, C-K theory was instead used to exploremarket opportunities. Figure 4 is an exampleof the C-K diagrams produced by one of theteams, utilizing C-K theory towards develop-ing a project concept. Figure 4 shows theexpansion of both knowledge in the K-space,and pathways in the C-space, as well as thelinks between the C and K spaces.

Data Collection

We collected our data in two ways: firstly, weanalysed the resulting C-K diagrams from theapplication of C-K theory through the frame-

work described in relation to Table 1. Secondly,we distributed a questionnaire to all of thenascent technology entrepreneurs, askingquestions about their experience of applyingthe C-K theory. The questionnaire had a 45%(27 of 60) response rate.

Data Analysis: A Combined Quantitativeand Qualitative Approach

Each team produced a C-K diagram. The 13C-K diagrams were then scored by two ratersindependently. To do so, the raters used theinterpretation of the five principles of causa-tion and effectuation based upon the analyticalframework presented in Table 1. For each C-Kdiagram, the raters had to score the C-Kdiagram according to the format presented inTable 2. Therefore, each diagram received acoupled score, one reflecting the use of causallogic, one reflecting the use of effectual logic.For example, if a team was seen to map bothspaces (= 1 effectual score), explore differentalternatives and build on value of the linkbetween C and K (= 1 effectual score), map theunknown missing knowledge and theunknown paths (= 1 effectual score), have nodisruptive concept (= 1 causal score), andpresent extensive K mapping (= 1 causalscore), they would receive a coupled score of(2,3): a causation score of 2 and an effectuationscore of 3. The ratings displayed satisfactoryinter-rater correlation (r = 0.92). There is con-siderable co-variation among both five factorsdetermining causation and the five factors cap-turing effectuation, but arguably not betweenthe two groups of factors. The factors are thusonly helping to detect occurrence of a logicand are only indicative of the magnitude of alogic used. An example scoring based on theteam example C-K diagram provided inFigure 4 is presented in Table 3.

To identify how the nascent technologyentrepreneurs perceived their use of causationand effectuation more in hindsight, the ques-tionnaire included both open-ended ques-tions, as well as one multiple-part Likert-scalequestion (see Appendix). The first three open-ended questions addressed how the nascenttechnology entrepreneur generally compre-hended C-K theory related to the SambaSensor case, in order to qualify that theresponse to the final questions were notimpeded by the use of C-K theory itself. Thefourth question addressed the nascent technol-ogy entrepreneur’s own interpretation of theirperformance in applying C-K theory towardsexploring the potential pathways of the tech-nology. The fifth and final question utilized aLikert-scale format, designed to investigateperceived use of C-K theory in terms of six



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different orientations: (a) action-orientation,(b) goal-orientation, (c) process-orientation, (d)product-orientation, (e) actor-orientation and(f) reflexively. Items (a), (c) and (e) are seen toalign with effectuation principles while items(b), (d) and (f) align with causation principles.Previous studies have applied similar data col-lection methods in order to assess the use ofcausal and effectual logics in decision makingtowards new venture or technological devel-opment (Chandler et al., 2011; Brettel et al.,2012; Harms & Schiele, 2012). Furthermore,the Likert-scale question mirrors a study con-ducted by Brettel et al. (2012), addressing theuse of causal and effectual logics relative toR&D project performance, as our respondentsare, like the Brettel et al. study, asked to evalu-ate preference towards causal or effectuallogics through a Likert scale format, as well assubjective performance evaluation. As for the

first part of the data analysis, this resulted incoding each participant responses based on theLikert-scale questions. Indeed, the responsesto parts (a)–(f) of the final question in the ques-tionnaire were utilized to establish a coupledscore (effectual score, causal score), where theeffectual score was the mean of the answersgiven in items (a), (c) and (e), while the meanof the score given in (b), (d) and (f) providedthe causal score.

Results

Coding C-K Diagrams and EvaluatingCausation and Effectuation

The 13 teams delivered analyses utilizing C-Kdiagrams. For each team/C-K diagram, aco-ordinate is generated from the coupledscore (effectual score, causal score), with

Table 2. Analytical Framework for a C-K Diagram

Causal logic No/Yes Effectual logic No/Yes

Map the knowledge space 0/1 Map both spaces 0/1Explore one linear path and

the value it holds (explore onepath in C)

0/1 Explore different alternatives and buildon value of the link between C and K(capability to shift design path)

0/1

Map the missing knowledge andthe existing alternatives

0/1 Map the unknown missing knowledgeand the unknown paths

0/1

No disruptive concept 0/1 Disruptive concept 0/1Control and anticipation of

all possible scenarios/Extensive K mapping

0/1 Robustness 0/1

Total 0/5 Total 0/5

Table 3. Example Data Analysis of a C-K Diagram

Causal logic No/Yes Effectual logic No/Yes

Map the knowledge space 0 Map both spaces 1Explore one linear path and

the value it holds (explore onepath in C)

0 Explore different alternatives and buildon value of the link between C and K(capability to shift design path)

1

Map the missing knowledge andthe existing alternatives

1 Map the unknown missing knowledgeand the unknown paths

1

No disruptive concept 0 Disruptive concept 1Control and anticipation of

all possible scenarios/Extensive K mapping

0 Robustness 0

Total 1 Total 4



minimum possible score of zero andmaximum possible score of five (using thescoring system from Table 2). The 13 coupledscores were then compiled to illustrate theoverall causal and effectual distribution acrossall 13 teams (Figure 5). In Figure 5, the x-axisrepresents the effectual score and the y-axisrepresents the causal score. The axes rangefrom zero to five to illustrate the score gener-ated for each team through the analyticalframework (Table 2), with the coupled scoreestablishing a co-ordinate relative to the x andy axes. The size of the dots is correlated withthe number of teams that generated the samecoupled score, such that a smaller circle wouldrepresent fewer teams with the same score,and a larger circle would represent a largernumber of teams with the same score.

Figure 5 shows that in applying C-K dia-grams to the sensor technology, the actions ofthe nascent technology entrepreneurs can beinterpreted as combining causation and effec-tuation, but with a greater emphasis on the useof effectual decision making.

Perception of Use

The responses to the final question in the ques-tionnaire establish a coupled score (effectualscore, causal score), generating a co-ordinate,shown in Figure 6. Figure 6 compares therespondent’s own perceived use of causal andeffectual decision making, as determined bythe coupled score. The same representationapplied in Figure 5 is also used in Figure 6;

thus, again the x-axis represents the effectualscore and the y-axis represents the causalscore, with the coupled score of each respond-ent generating a co-ordinate presented in thefigure. Again, similar to the format of Figure 5,the size of the dots in Figure 6 is correlatedwith the number of respondents that werecoded with the same coupled score.

Figure 6 illustrates that respondents tendedto interpret their perceived use of C-K dia-grams towards decision making as causallyoriented more than effectually oriented.

In comparison, Figures 5 and 6 differ asregards occurrence of causation and effectua-tion. The questionnaire, which was answeredin hindsight (Figure 6), indicates mainly use ofcausal logic, whereas use of effectual logic isseen to occur more extensively when interpret-ing the use of C-K diagrams (Figure 5). Theseresults thus suggest a gap between thedecision making actually done (being moreeffectual) and how the nascent technologyentrepreneurs in hindsight perceive theirown decision making (stated in more causalterms).

Discussion and Conclusions

The purpose of this article is to exploremindful deviation in technology entrepre-neurship as decision making combining causaland effectual logics. First, the discussion willinvestigate the relevance of a decision-making

Figure 5. Primary Analysis of the Outcomes of Applying Design Theory-Driven Methodology:Effectual-Causal Coupled Score



approach. Following this, four aspects relatedto the occurrence of effectual and causal logicwill be analysed.

Previous studies into technology entrepre-neurship basically have understood early-stage deviation into new opportunities as adiscrete creative event and not as a decision-making process. Prior knowledge of an area(Shane, 2000) as well strong pattern-recognition capabilities (Baron, 2006) are iden-tified factors behind successful opportunityrecognition. Through C-K design theoryapplied by 13 teams of nascent technologyentrepreneurs upon the same innovation, amethod for detecting decision making is intro-duced. Even though prior knowledge amongthe 13 teams can be considered moderate, themajority are still able to deviate substantiallyfrom their original platform technology into avariety of different product concepts. Thisdeviation is also clearly traceable through theC-K diagrams, in which different concepts arelogically interrelated in the C-space whileknowledge expansions occur in the K-space. Itcan thus be concluded that deviation in early-stage technology entrepreneurship can becharacterized as a decision-making processengaging a team (thus being collective) withmoderate prior knowledge, rather than assomething singular, individualistic anddepending upon prior knowledge.

Given, the exploratory and experimentalcharacter of the study, there are some limita-tions to this main conclusion. Firstly, althoughthe nascent entrepreneurs were asked both for

C-K maps and written accounts around theprocess, it is not possible to fully determinehow much these delivered outputs actuallyrepresent the process and how much they areafter-rationalizations of something that mighthave occurred more individualistically andsingularly. Secondly, while the concept ofmindful deviation comes from entrepreneursarguing for and legitimizing a path-breakingsolution, the current study does not take intoaccount any subsequent progress and realiza-tion of a chosen opportunity. It merely reportsthat C-K diagrams indicate use of decisionmaking during an early opportunity-recognizing stage. However, given these limi-tations and the obvious need for furtherstudies, the richness and variety foundthrough applying C-K diagrams in early-stagetechnology entrepreneurship does suggestthat a more singular, individualistic anddiscovery-oriented (rather than a collectivedecision-making-oriented) view on technol-ogy entrepreneurship can be questioned.

Effectuation Occurring amongNascent Entrepreneurs

Previous research into effectuation associateseffectual logic with experienced entrepreneurs(Sarasvathy, 2001; Read and Sarasvathy, 2005;Dew et al., 2009). This study shows thatnascent entrepreneurs also use effectual logic.Whether this is due to the application of C-Ktheory, or whether this would have been thecase regardless of the method used, is difficult

Figure 6. Supporting Analysis of the Outcomes of Applying Design Theory-Driven Methodology:Perception of Use



to say. However, our study suggests that effec-tual logic should subsequently be associatednot only with experience and seniority. Rather,effectual logic can also occur – either naturallyor induced through method – among individ-uals lacking entrepreneurial experience. Thisarguably widens substantially ‘the populationof effectuators’, while demystifying this typeof decision making as not depending signifi-cantly upon expertise and certain experiences.

Hindsight Bias Disguises Effectuation

Results from the questionnaire indicate thatuse of effectual logic is more difficult to detectin hindsight. Whether this is due to the nascenttechnology entrepreneur lacking sufficientskill, experience or language to appreciate aneffectual logic, or whether such hindsight biasalways would occur, is not possible to deter-mine through the current study. Nevertheless,this differentiation between the applicationversus perceived use of effectual logic is notaddressed in previous studies of effectuation(e.g., Dew et al., 2009). There is thus strongreason to continue exploring more interactive(rather than ex post) measurement of effectuallogic if we want to capture its occurrence andrelevance. Interactive measurement may alsohelp to avoid a hindsight bias, through whichhumans simplify and rationalize in order tomake sense of a more complex and fluidexperience (Kahneman & Riepe, 1998). In con-clusion, our study suggests that effectuationoccurs much more in action than is possible todetect in hindsight, adding to the previousconclusion that this decision-making logicshould be demystified and not solely associ-ated with experts or previous experience.

Expanding Mindful Deviation intoOpportunity Recognition

The tracing of decision making through C-Kdiagrams adds to our understanding ofmindful deviation. The concept of mindfuldeviation has been associated with later stagesof technology entrepreneurship, where theneed to convince others to join or buy into achosen novel path is essential (Garud &Karnøe, 2001a). The current study expandsmindfulness into the early concept-generativephase of technology entrepreneurship, wheremindfulness was observed as effectual andcausal decision making. So, while mindfuldeviation has been more readily associatedwith individual technology entrepreneurscommunicating to and convincing others, thecurrent study instead emphasizes the inclu-sion of persons into a more collective andopen-ended decision making, which precedesany subsequent and perhaps more persuasive

process. Although this is a shift in perspective(from convincing to making decisions) andincludes earlier stages (opportunity recogni-tion), we propose that the concept of mindfuldeviation remains highly relevant and is evenenriched through the current study. Futurestudies into technology entrepreneurship as aprocess ought to benefit from focusing moreon the process of collective and mindfularticulation, whether for explorative (decisionmaking) or more exploitative (convincing andinfluencing) purposes.

Mindful Deviation as CombiningEffectuation and Causation

Finally, the interpretation of the C-K diagramsrelative to effectuation and causation canincrease our understanding of how the twologics can be combined. The factors used todefine effectuation and causation (Table 1)arguably imply that path deviation requireseffectuation. Effectuation deals with startingwith means while keeping ends open, as wellas allowing contingencies to trigger imaginaryrethinking. Causation, on the other hand,assumes ends and objectives to be fixed orpredetermined. Hence, it is perhaps not sur-prising to find more effectual logic occurringin the C-K diagrams. However, without anycausal logic illustrated in the C-K diagrams,the notion of mindfulness, including beingable to make and communicate consciousdecisions, would be hampered due to lack ofconsequential reasoning and inability tocompare different choices. Combining effec-tuation and causation then comes close to thetype of strategic decision making proposed as‘the science of muddling through’ (Lindblom,1959, 1979) or ‘logical incrementalism’ (Quinn,1978). As far as we are aware, early-stageopportunity recognition has not previouslybeen associated with such strategy-makingconcepts. Rather early-stage opportunity rec-ognition has been said to be reliant uponappreciation of the insightfulness of expertswith certain pattern-recognition capabilities.In essence, the combination of causal and effec-tual thinking displayed by all 13 teams helpedcreate a more holistic map in which conse-quential paths as well as path deviations areincluded.

The variety of application ideas traced usingC-K diagrams should thus be ascribed notonly to the use of effectuation, but rather to thecombination of both causation and effectua-tion. For example, sometimes the teams con-verged on a goal, and then elaborated on thegoal further. Other times, it is obvious thatnew concepts emerged through effectual deci-sion making and were then translated as a goal



once identified. In conclusion, the combinationof effectuation and causation reflects that(nascent) technology entrepreneurs arerequired to address both existing tech-nological paths and novel entrepreneurialdevelopments, and that they benefit fromdecision-making processes more similar tostrategy making than to singular events ofindividual insightfulness.

Limitations and Next Steps

There are several limitations to our study. Thecurrent study is local and contextual andrequires further validation to substantiateclaims that effectual decision making is usedby early-stage technology entrepreneurs(Chandler et al., 2011; Perry, Chandler &Markova, 2011). Our study of the decision-making behaviour of (nascent) technologyentrepreneurs is, through the first level ofanalysis, based on coding the outcome of fourdays of work on a design theory-based inter-pretation of the two types of decision making(causal and effectual). This experimentalsetting is of course limited in time as well as inrealism (the entrepreneurs knew this was ashelved innovation, and thus not completely‘real’). Nevertheless, the setting is illustrativeof early-stage technology entrepreneurship,mirroring initiation of venture creation. Theinterpretative means for determining causaland effectual logics, the second level of analy-sis, while based on previous work, could alsobenefit from further testing.

A second limitation is the lack of a controlgroup (such as more traditional engineers,consultants, etc.). The study could potentiallybenefit from having a control group to deter-mine if the participants in the current study,as a population, have a specific mind-setwhich might bias their application and/or per-ception one way or another. The teams weremostly hybrids, with team members havingengineering or business degree backgrounds.However, our study has traced mindful devia-tion in a population intending to (at least)become entrepreneurial (if not entrepreneurs).Studying groups lacking such ambition maynot provide relevant insight into entrepreneur-ial decision-making processes, as these groupsmight lack the agency emphasized in the exist-ing literature.

Our study was conducted on technologyentrepreneurship students due to the easyaccess to this specific population. However,such a selection in our data sample might notreflect both the actions and the perceptionof these actions of more mature and experi-enced technology entrepreneurs. Yet it allows

elaboration on future hypotheses for thecurrent understanding of nascent technologyentrepreneurs. Facilitating traceable consciousdecision-making processes of technologyentrepreneurs may also allow us to increasegeneral understanding of entrepreneurial cog-nition, as explored in the work of Mitchellet al. (2007).

Finally, although the current study indicatesbehavioural preference towards effectuationand cognitive preference towards causation,this should not automatically favour one atthe expense of the other. Rather, C-K theory,through C-K diagrams, seems to offer a valu-able tool to further explore actual entrepre-neurial behaviour as well as entrepreneurialperception and identity. The current studyshows that even a simulated setting can offersome insights. Further studies could look intouse of C-K diagrams more longitudinally aswell as related to more real-life entrepreneur-ship situations.

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Marine Agogué ([email protected]) isan assistant professor in innovation man-agement at HEC Montréal and is a memberof the Chair Design Theory and Methodsfor Innovation at Mines ParisTech. Sheworks on fixation effect in creativity and oncognitive bias in innovation. Her work hasbeen published in journals such as Journalof Creative Behavior, International Journal ofInnovation Management and TechnologyAnalysis & Strategic Management.

Mats Lundqvist ([email protected]) is Professor in Entrepreneur-ship at Chalmers University of Technology,as well as the director and co-founder (in1997) of Chalmers School of Entrepreneur-ship, the top-ranked entrepreneurshipinstitution in Sweden. Research interestsinclude university entrepreneurship,academic entrepreneurship, incubationpractice, action-based entrepreneurshipeducation as well as institutional transfor-mations. His work has been published in,for example, Research Policy, Science andPublic Policy, R&D Management andTechnovation.

Karen Williams Middleton ([email protected]) is an associate pro-fessor in entrepreneurship at ChalmersUniversity of Technology, with researchinterests in the areas of nascent entrepre-neurship, entrepreneurial identity andbehaviour, entrepreneurial learning andeducation, and university entrepreneur-ship. Her work has been published in, forexample, Journal of Small Business and Enter-prise Development, International Journal ofEntrepreneurial Behaviour Research and Inter-national Journal of Entrepreneurship and Inno-vation Management.

Appendix

Question 1. Was C-K theory useful for theSamba Sensor case?Question 2. Was C-K theory easy tounderstand?Question 3. Was the amount of introduction toC-K theory sufficient?Question 4. Describe in your own words howyou applied C-K theory.Question 5. On a scale of 1(low) to 5 (high),how did you apply C-K theory, in terms of thefollowing:a. from an action-oriented perspectiveb. from a goal-oriented perspectivec. from a process-oriented perspectived. from a product/service oriented

perspectivee. from an actor-oriented perspectivef. reflexively



mindful deviation through combining causation and...

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