Conference Agenda

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Session Overview
19-AM-04: ST6.3 - The Management of Uncertainties in Innovation Activities
Wednesday, 19/June/2019:
8:30am - 10:00am

Session Chair: Leonardo Augusto De Vasconcelos Gomes, Universidade de Sao Paulo
Session Chair: Mario Sergio Salerno, University of São Paulo, Polytechnic School
Location: Amphi Poisson

Session Abstract

Managing Radical innovation (RI) in large mature companies requires addressing high levels of uncertainties, not only risks. The literature recognizes that firms should build special capabilities to manage RI initiatives (O’Connor et al. 2008, 2018; Bagno et al 2017; Salerno et al 2015). Although grounded theoretical and empirical frameworks exist in the literature for understanding the dynamics of RI’s (e.g. O’Connor&Rice 2013), firms still struggle to deal with the complex uncertainties landscape that RI’s present (Brasil et al. 2018, Eggers&Kaul 2018). Recent studies call for a more systematic approach for confronting uncertainties. For example, new project management processes have been proposed (Rice et. al. 2008). At a systems level, Gomes et al. (2018) proposed a framework for managing uncertainties in the ecosystem; O’Connor et al (2008) propose the emergence of an Innovation Function (IF) in mature companies; O’Connor et al (2018) discuss IF managerial roles; Salerno&Gomes (2018) propose a networked IF in companies; Lubik et al (2013) analyse value creation in university spin offs. These studies open opportunities for further research, drawing upon new theoretical and methodological perspectives.

In this track, we are interested in moving the frontier of knowledge forward by addressing, from different theoretical perspectives, how innovative firms – whether mature or knowledge intensive startups–manage uncertainties associated with radical innovations. We are especially interested in the following topics:

1. What are the types of uncertainties that RI project teams and start-ups face?

2. Which contingencies moderate the ways firms should organize for RI to best cope with uncertainties?

3. How should companies manage uncertainties within innovation ecosystems?

4. How does uncertainty affect the way firms negotiate contracts with external partners for RI projects?

5. How do firms manage the uncertainties present in RI projects at the portfolio level?

6. What firm level capabilities are required to overcome uncertainties present in RI’s?

7. What skills and capabilities are required of managers and entrepreneurs to deal with uncertainties?

8. What heuristics do entrepreneurs or managers use for perceiving and managing uncertainties?

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How Goal Orientation can help managers navigate the fuzzy front end of innovation

Peter Robbins1, Colm O'Gorman2, Anne Sigismund Huff3

1DCU DOT Lab; 2Dublin City University; 3Dublin City University


The Front End is, paradoxically, both the most important and least studied phase of the innovation process: it is characterised by extreme ambiguity and uncertainty. Researchers are increasingly turning to cognitive approaches and this paper provides the first evidentiary support for the link between learning goal orientation and radical innovation.


Literature reviewed in this case study includes:

1) Radical Innovation Literature (Colombo et al., 2017; Christensen, 1997; Leifer et al., 2000; Pérez‐Luño et al., 2011; O’Connor and DeMartino, 2006)

2) Innovation in Teams (Koen et al, 2014 a&b; Im et al, 2013; Wuchty et al 2007; Patanakul et al, 2012; Pah et al, 2018)

3) Front end of Innovation (Reid and Bretani, 2004: Hansen and Birkinshaw, 2007; Aagaard and Gertsen, 2011; Haase and Laursen, 2018)

4) Innovation Models to reduce uncertainty (Bagno et al, 2017; Velamuri et al, 2017; Schweitzer et al, 2018)

5) Cognitive Drivers of Innovation (Lu et al., 2015; Nakata and Im, 2010; Cowlrick et al, 2011)

6) Goal Orientation Theory (Alexander and Von Knippenberg, 2014; Dweck, 1986)

Literature Gap

Alexander and Von Knippenberg (2014) have suggested a link between a learning or mastery goal orientation and radical innovation and this paper provides the first empirical evidence to test that hypothesis.

Research Questions

When managing the front end of innovation, in a large, complex, global, pharma company where the quest is, not just, a high level of novelty (radical innovation) but also delivered under acute time pressure: can a shared team goal orientation steer a team towards either radical or incremental innovation?


This is an inductive, revelatory case-study which focuses on goal orientation during the fuzzy front end of an innovation process. Our primary data is drawn from a more extensive study of innovation in the context of a one of the world’s top three pharma firms (referred to as Pharmaco). In this paper we focus on the teams involved in an organisational experiment, what we refer to as the Radical Innovation Tournament (RIT), based in the R&D division of Pharmaco. This division operated primarily in the UK and the US, with over 300 R&D staff based in each country.

Empirical Material

The company fielded an organisational experiment which was intended to stimulate radical innovation in a competitive way. They put two teams (of ~12 PhD scientists) together; one in the UK and one in the US and gave them an identical brief - to come up with radical, game changing ideas for the company. This study draws on 32 in-depth interviews conducted over a six-year period.

Analysis of the data followed processes used in analyzing qualitative data (Miles and Huberman, 1994; Yin, 2003). Analysis began with the transcribing of all interview data. This was followed by writing detailed histories or narratives of the two teams, using both the interview data and secondary data. In analysing the data we sought to identify each team’s shared goal orientation and the team leader’s goal orientation. We used the categories and aggregate theoretical dimensions proposed by Alexander and van Knipperberg (2014) to structure our coding. This involved reviewing all transcripts to identify quotes that reflected goal orientation, be it a mastery or a performance goal orientation.


The UK team was characterised by a shared learning goal orientation , while the US team was characterised by a shared performance goal orientation. In summary, the UK team focused on new knowledge; new technology and novel ideas, with any consideration of consumer preference, or possible ‘market-fit’, or value-proposition relegated to a very secondary position. In terms of process, the UK team allowed ideas emerge on the basis of individual team member passion for an idea; did not assign team roles (with the exception of team leader which was assigned by senior management prior to team formation); and they did not set any milestones (again with the exception of the externally imposed nine month timeframe for completing the project).

In contrast, the US team was categorised as having a shared performance goal orientation. In summary, the US team adopted a very tightly structured approach, putting the consumer at the heart of the process (while effectively relegating the quest for novel science to a secondary position). The process they adopted began with a firm plan of how to look better in the grand-finale presentation; how to avoid the embarrassment of being defeated in the competition - in short, how to win.

Contribution to Scholarship

This is the first paper to provide evidential support to the link between radical innovation and learning goal orientation as hypothesised by Alexander and van Knippenberg (2014). Furthermore, we extend Alexander and van Kippenberg’s argument to suggest that there is a corollary proposition that a shared team performance goal orientation may be effective in producing incremental innovation. This is significant because most New Product Development activity is aimed at incremental innovation (Veryzer, 1998).

Second we further illustrate the potential usefulness of abductive research. We started with a theory based view of the outstanding issues in FEI research. Once we had detailed information from an intensive study of a corporate experiment in the area, we were able to look farther afield. Goal theory made sense given how much attention individuals and team members spent on thinking about and framing what they were trying to do and what they were getting done.

Contribution to Practice

Managers need to make innovation more systematic. Ideally, they want to create a capability for their organisation which produces a pipeline of innovation which is predictable and scalable. The Front End of innovation is risky. The information upon which commercial decisions would normally be made is either absent or unclear. Scholars have proposed many strategies to help reduce this uncertainty but none have found widespread traction. This paper shows how by framing the goal orientation of the leader and of the team, managers can choose whether they want them to deliver radical or incremental innovation.


The Pharma industry is one which depends, more than many others, upon innovation for its survival. Being able to navigate the Front End is vital for firm survival. This paper looks at the Front End of Innovation and explore a cognitive and mindset-driven approach to targeting radical innovation.


Aagaard, A. & Gertsen, F. 2011, "Supporting Radical Front End Innovation: Perceived Key Factors of Pharmaceutical Innovation", Creativity & Innovation Management, vol. 20, no. 4, pp. 330-346.

Alexander, L. & van Knippenberg, D. 2014, "Teams in Pursuit of Radical Innovation: a Goal Orientation Perspective", Academy of Management Review, vol. 39, no. 4, pp. 423-438.

Bagno, R.B., Salerno, M.S. & da Silva, D.O. 2017, "Models with graphical representation for innovation management: a literature review", R&D Management, vol. 47, no. 4, pp. 637-653

Christensen, Clayton M. (1997) The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail. Boston, MA: Harvard Business School Press, 1997

Colombo, M.G., von Krogh, G., Rossi-Lamastra, C. & Stephan, P.E. 2017, "Organizing for Radical Innovation: Exploring Novel Insights", Journal of Product Innovation Management, vol. 34, no. 4, pp. 394-405.

Cowlrick, I., Hedner, T., Wolf, R., Olausson, M. & Klofsten, M. 2011, "Decision-making in the pharmaceutical industry: analysis of entrepreneurial risk and attitude using uncertain information", R&D Management, vol. 41, no. 4, pp. 321-336.

Dweck, C.S. 1986, "Motivational processes affecting learning", American Psychologist, vol. 41, no. 10, pp. 1040-1048.

Haase, L.M. & Laursen, L.N. 2018, "Reasoning in the Fuzzy Front End of Innovation: Framing the Product Dna", International Journal of Innovation Management, vol. 22, no. 5, pp. N.PAG-N.PAG.

Hansen, M. T. and Birkinshaw, J. (2007) ‘The Innovation Value Chain’, Harvard Business Review, 85(6), pp. 121–130.

Im, S., Montoya, M.M. & Workman, J.P. 2013, "Antecedents and Consequences of Creativity in Product Innovation Teams Antecedents and Consequences of Creativity in Product Innovation Teams", Journal of Product Innovation Management, vol. 30, no. 1, pp. 170-185.

Koen, P.A., Bertels, H.M.J. & Kleinschmidt, E. 2014, "Managing the Front End of Innovation-Part I", Research Technology Management, vol. 57, no. 2, pp. 34-43.

Koen, P.A., Bertels, H.M.J. & Kleinschmidt, E.J. 2014, "Managing the Front End of Innovation–Part II", Research Technology Management, vol. 57, no. 3, pp. 25-35.

Koen, P., Ajamian, G. & Burkart, R. 2001, "Providing clarity and a common language to the “fuzzy front end", Research Technology Management, vol. 44, no. 2, pp. 46-55.

Leifer, R., McDermott, C.M., O'Connor, G., Peters , L., Rice, M.P. & Veryzer , R. 2000, Radical Innovation: How Mature Companies Can Outsmart Upstarts, First edn, Harvard Press, Boston, Mass.

Lu, L., Lin, X. & Leung, K. 2012, "Goal orientation and innovative performance: The mediating roles of knowledge sharing and perceived autonomy", Journal of Applied Social Psychology, vol. 42, pp. E180-E197.

Nakata, C. & Im, S. 2010, "Spurring Cross-Functional Integration for Higher New Product Performance: A Group Effectiveness Perspective", Journal of Product Innovation Management, vol. 27, no. 4, pp. 554-571.

O'Connor, G.C. & DeMartino, R. 2006, "Organizing for Radical Innovation: An Exploratory Study of the Structural Aspects of RI Management Systems in Large Established Firms", Journal of Product Innovation Management, vol. 23, no. 6, pp. 475-497.

Pah, A., Uzzi, B. & Hinds, R. 2018, "A Study of Thousands of Dropbox Projects Reveals How Successful Teams Collaborate", Harvard Business Review Digital Articles, pp. 2-5.

Patanakul, P., Chen, J. & Lynn, G.S. 2012, "Autonomous Teams and New Product Development Autonomous Teams and New Product Development", Journal of Product Innovation Management, vol. 29, no. 5, pp. 734-750.

Pérez-Luño, A., Medina, C.C., Lavado, A.C. & Rodríguez, G.C. 2011, "How social capital and knowledge affect innovation", Journal of Business Research, vol. 64, no. 12, pp. 1369-1376.

Reid, S.E. & de Brentani, U. 2004, "The Fuzzy Front End of New Product Development for Discontinuous Innovations: A Theoretical Model", Journal of Product Innovation Management, vol. 21, no. 3, pp. 170-184.

Schweitzer, F., Palmié, M. & Gassmann, O. 2018, "Beyond listening: the distinct effects of proactive versus responsive customer orientation on the reduction of uncertainties at the fuzzy front end of innovation", R&D Management, vol. 48, no. 5, pp. 534-551.

Velamuri, V.K., Schneckenberg, D., Haller, J. & Moeslein, K.M. 2017, "Open evaluation of new product concepts at the front end of innovation: objectives and contingency factors", R&D Management, vol. 47, no. 4, pp. 501-521.

Wuchty, S., Jones, B.F. & Uzzi, B. 2007, "The Increasing Dominance of Teams in Production of Knowledge", Science, vol. 316, pp. 1036-1039.

Measuring the immeasurable? Explaining Intuitive Judgments Through Experimental Research Designs

Carlos Vazquez Hernandez, Massimo Garbuio, Betina Szkudlarek

University of Sydney Business School, Australia


Experimental designs are rarely used in innovation management research. This is evident when investigating the cognitive aspects of managing innovation such as heuristics and it consequent intuitive judgments. Scholars can access different guides from other disciplines for designing experiments. However, one that reflects the challenges in innovation management is missing.


Advocating for the use of experimental research in the study of innovation management is not new. Recently, there have been calls to consider the benefits of experiments to study the complexity of innovation processes. Related disciplines, such as entrepreneurship, have advocated using experiments and provided entrepreneurship scholars with a typology of experimental treatments to improve rigour and validity. However, innovation management scholars lack a guide to understand how to use experiments in the context of innovation, especially for understanding the causal relationships of intuitive judgements in an innovation project. This limits our capacity to identify the factors that underlie the role of intuition in innovation management, and we must rely only on correlational descriptions, and/or exploratory discoveries. Experiments provide the opportunity to inductively conclude causal relationships beyond mere simultaneous occurrences and exploratory ideas and enables us to measure the probability that a given cause is behind a given effect.

Literature Gap

In our research of documents dealing with intuition and innovation, we found that only 3/31 are experimental.This small proportion of articles might be because innovation management scholars do not have a guide explaining how the seven dimensions of the experimental method operate in the context of decision making.

Research Questions

What does a guide to conduct experimental research looks like in the context of intuitive decision making in innovation management?


This is a conceptual paper that consolidates and aggregates various research sources regarding the key seven dimensions that an experimental research should contain, and without which causation cannot be inferred. It contextualises these dimensions using the instance of intuitive decision making in innovation management. This is because through knowing how to conduct experiments, innovation management scholars can infer the causes behind the making of rapid, automatic, holistic, and nonconscious decisions while managing an innovation project. This is important to understand for unveiling some of the cognitive aspects of managers making decisions while managing uncertain situations and activities in innovation.

Empirical Material



The experimental method intrinsically contains four elements. It is deterministic, empirical, parsimonious, and testable. It is deterministic because the level of certainty is defined by statements of cause-and-effect that assume definite values . It is empirical because the evidence provided by an experimental research is acquired by collecting data through structured observation, and/or experiencing a particular phenomenon. It is parsimonious because it tends towards providing simple and straightforward explanations to a given phenomenon. It is testable because it requires the examination of empirical data to support or reject a given (null) hypothesis, and because of its capacity for replication and falsifiability. Issues with replicability and falsifiability are sine qua non to understand and implement in conducting experiments to ensure rigour and avoid legitimacy questions. As a structured approach, the dimensions that encompass the method are: (1) the type of experiments; (2) experimental setting; (3) experimental design, (4) sample; (5) treatments (manipulations); (6) confounding influences (i.e. extraneous variables); and (7) validity checks. We considered these dimensions to be fundamental experimental components that a sophisticated and rigorous experiment should include. Through these dimensions, we can have a view about what an experimental research entails.

Contribution to Scholarship

We contribute to the field of innovation management research by providing a perspective of how its cognitive aspects such as intuitive decision making could be scientifically investigated and measured through experimental research designs. For example, we can study the probability that a given heuristic (e.g. representativeness) is driving intuitive judgments in innovation management.

Contribution to Practice

In spite being a conceptual paper aimed at scholars, practitioners could look at the experimental dimensions as a tool to evaluate rigour behind explanations of causal inferences while making decisions in innovation management, and further reflect upon what those inferences mean in the context of their own rules of thumb that drive some of their intuitive judgments while dealing with an innovation project.


This paper contributes to the management of uncertainties in innovation discussion. Particularly because, the paper deals with the need to understand the role that intuition has in innovation management, and how the use experimental research designs can help us to make causal inferences as to the heuristics behind intuitive judgements.


Adams, J., Khan, H.T.A., Raeside, R., 2014. Research Methods for Business and Social Science Students. SAGE Publications, New Delhi.

Atmanspacher, H., Bishop, R., 2014. Between Chance and Choice: Interdisciplinary Perspectives on Determinism. Andrews UK Limited.

Cook, T.D., Campbell, D.T., Shadish, W., 2002. Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin Boston.

Cooper, D.R., Schindler, P.S., Sun, J., 2006. Business research methods. McGraw-Hill, Irwin, NY, US.

Drabinski, J.E., 1993. Radical Empiricism and Phenomenology: Philosophy and the Pure Stuff of Experience. J. Specul. Philos. 7, 226–242.

Ewert, A., Sibthorp, J., 2009. Creating outcomes through experiential education: The challenge of confounding variables. J. Exp. Educ. 31, 376–389.

Gigerenzer, G., Selten, R., 2002. Bounded rationality: The adaptive toolbox. MIT press.

Harrison, G.W., List, J.A., 2004. Field experiments. J. Econ. Lit. 42, 1009–1055.

Hsu, D.K., Simmons, S.A., Wieland, A.M., 2016. Designing Entrepreneurship Experiments: A Review, Typology, and Research Agenda. Organ. Res. Methods

Ioannidis, J.P., 2005. Why most published research findings are false. PLoS Med. 2, e124.

Kirk, R.E., 2013. Experimental design. SAGE Publications.

Pashler, H., Wagenmakers, E.-J., 2012. Editors’ introduction to the special section on replicability in psychological science: A crisis of confidence? Perspect. Psychol. Sci. 7, 528–530.

Schlesselman, J.J., 1978. Assessing effects of confounding variables. Am. J. Epidemiol. 108, 3–8.

Sekaran, U., Bougie, R., 2016. Research Methods For Business: A Skill Building Approach. John Wiley & Sons.

Sørensen, F., Mattsson, J., Sundbo, J., 2010. Experimental methods in innovation research. Res. Policy 39, 313–322.

Tversky, A., Kahneman, D., 1974. Judgment under Uncertainty: Heuristics and Biases. Science 185, 1124–1131.

How to enroll industrial collaborators in the nascent academic entrepreneurship under uncertainty: a dynamic commitment model

Peisi Lin, Wei Liu, Jihai Jiang

School of Economics and Business Administration, Chongqing University, China


We put forward novel uncertainties in the nascent process of academic entrepreneurship, and then flesh out a conceptual commitment model to explain how the academic entrepreneurs who aim at commercializing the research and development achievement to enroll industrial collaborators.


The ideal way for inventors (academic entrepreneurs) to commercialize high-tech innovation achievements is to create a new venture together with industrial entrepreneurs who are well equipped with market knowledge (Würmseher, 2016). However, in the process of nascent entrepreneurship, multiple founders confront with high uncertainty when making decisions to cooperate, accounting for the drastic changes of competitive environment, the cognitive limitations between entrepreneurs and the lack of vital information (Hopp, 2015). Relevant work on teams in operating firms suggests that commitment, a conception closely related to collaborators enrollment, can help people to work together effectively (Klein, 2012). Nevertheless, we know little about how multiple founders work through the commitment processes under high uncertainty that may shape their cooperative efforts, including how they come to a working consensus around how to move forward (Powell, 2017).

Literature Gap

Research has far focused on exploring the baseline case of ventures dominated by a single founder but little is known about multi-founder's nascent entrepreneurship development. Moreover, little previous literature has examined the particular uncertainties associated with co-operative relations in the settings of academic entrepreneurship.

Research Questions

1.What kinds of uncertainties the academic entrepreneurs face when enrolling industrial collaborators in the nascent entrepreneurship?

2.What measures can academic entrepreneurs take to deal with the specific uncertainty?

3.How to describe the specific process of commitment between academic entrepreneurs and industrial collaborators?


In this research, we use theoretical analysis and empirical method comprehensively. As systematically reviewing the literature of uncertainty and exploring complex real-world phenomena, we not only conceptualize the uncertainty under the context of academic entrepreneurship but also propose a theoretical model for commitment. In addition, to explore why uncertainty has deep impacts on decision-making process and how to eliminate the obstacles, we utilize the tentative method of case study to unfold the complex and concrete mechanism. At last we offer a solid case called Royole from China to describe, illustrate and analyze the theoretical hypothesis and the model framework.

Empirical Material

In this research, we use theoretical analysis and empirical method comprehensively. As systematically reviewing the literature of uncertainty and exploring complex real-world phenomena, we not only conceptualize the uncertainty under the context of academic entrepreneurship but also propose a theoretical model for commitment. In addition, to explore why uncertainty has deep impacts on decision-making process and how to eliminate the obstacles, we utilize the tentative method of case study to unfold the complex and concrete mechanism. At last we offer a solid case called Royole from China to describe, illustrate and analyze the theoretical hypothesis and the model framework.


We define and delineate novelty types of uncertain for academic entrepreneurs in the cooperative entrepreneurship contexts: the struggles to establish social ties with potential collaborators and hardness to strengthen the cooperative relationship. In developing our theory, we employ a two-stage model to uncover how academic entrepreneurs intentionally target desired pre-commitment towards industrial collaborators and then how they achieve sustained commitment to ultimately set up a company. Herein, we add important insights to complete the model. On one hand, individual proximity provides an important path for network construction and is regulated by heritage in the former stage. On the the hand, sufficient information feedback and knowledge sharing are required to engage both of them in the entrepreneurial journey in the latter one. Overall, we put forward the conceptual the model to illustrate this process and take a typical example called Royole from China to understand it better.

Contribution to Scholarship

Firstly, most research to date presents an incomplete picture of multi-founder's entrepreneurship,and we contribute to expanding its focus to consider the cooperative relationship between academic and industrial entrepreneurs. Secondly, we demonstrate the novelty uncertainty when the academic entrepreneurs are intended to enroll industrial entrepreneurs. Meanwhile the conceptual model is proposed to explore implications for decision-making behaviors in the academic entrepreneurship over time. Thirdly, for commitment research, we unfold a more dynamic mechanism to understand why industrial collaborators receive a pre-commitment, and how the process of continuous commitment would strengthen their bonds to form a venture together. Moreover, the theory also links to and extends research about the integration of psychological and network perspectives in entrepreneurship studies. Overall, these insights help to construct a more refined and robust framework for analyzing the commitment process under high uncertainty.

Contribution to Practice

The paradigm of cooperative entrepreneurship we propose has access to heterogeneous resources and information, so there will be more opportunities and possibilities for entrepreneurs to share their knowledge and experience with each other, which will help the new venture to leap over the valley of death. Indeed, for scholars who are intended to commercialize their high-tech innovations, we provide operative and effective means, such as proximity and heritage to attract entrepreneurs from industry.


For academic entrepreneurs who come from universities, the sources of innovation, it is indeed a hard nut to bring the innovations out of laboratories with insufficient market experience and resources. Therefore, we pay attention to uncertainties they are facing and give inspired insights to cope with them.


Burns, B. L., Barney, J. B., Angus, R. W., & Herrick, H. N. (2016). Enrolling Stakeholders under Conditions of Risk and Uncertainty. Strategic Entrepreneurship Journal, 10(1), 97-106

Dangelico, R., Garavelli, A., & Petruzzelli, A. (2010). A System Dynamics Model to Analyze Technology Districts' Evolution in a Knowledge-Based Perspective. Technovation, 30,142–153.

Hopp, C. , & Sonderegger, R. . (2015). Understanding the dynamics of nascent entrepreneurship—prestart‐up experience, intentions, and entrepreneurial success. Journal of Small Business Management, 53(4), 1076–1096.

Klein, H. J. , Malloy, J. C. , & Brinsfield, C. T. . (2012). Reconceptualizing workplace commitment to redress a stretched construct: revisiting assumptions and removing confounds. Academy of Management Review, 37(1), 130-151.

Packard, M., Clark, B., & Klein, P. (2017). Uncertainty Types and Transitions in the Entrepreneurial Process, Organization Science, 28(5), 840-856.

Powell, E. E. , & Baker, T. . (2017). In the beginning: identity processes and organizing in multi-founder nascent ventures. Academy of Management Journal, 60(6), 2381-2414

Würmseher, M. (2016). To each his own: Matching different entrepreneurial models to the academic scientist's individual needs. Technovation, 59, 1-17

Zacharakis, A. L., & Shepherd, D. A. (2001). The nature of information and overconfidence on venture capitalists' decision making. Journal of Business Venturing, 16(4), 311-332

Dyads in innovation: when the best partner is the one you would not choose

Paola Bellis, Roberto Verganti

Politecnico di Milano, Italy


Innovation is the result of collaboration; it needs for social interaction to grow and become a reality.

In this paper, by focusing on dyads as an intermediate step before to enter a larger team, we investigate how cognitive distances affect the collaborative-sensemaking process people pass through when shaping breakthrough directions.


The development of shared innovative direction consists in a shared cognitive process where the people involved mutually develop and create a shared understanding that provides the basis for action (Pearce and Ensley 2004; Cox et al. 2003). It deals with the concepts of opportunity identification (Eling & Herstatt, 2017), vision development (O’Connor& Veryzer 2001) or direction development (Verganti, 2017).

Scholars consider the development of innovative shared directions as a collaborative sensemaking process (Kijkuit & van den Ende 2007; Nooteboom, 2000). Sensemaking is a cognitive and emotional process through which people make sense of their surroundings and act accordingly (Weick et al. 2005; Fellows, Liu, 2016). On a collective perspective, people make meaning socially by sharing experiences, visions, and converging on a common interpretation (Berger & Luckman, 1966; Goodman, 1978). However, the process is not free of tensions, which could compromise the collaborative sensemaking process itself (Weick and Westley, 1996).

Literature Gap

To overcome sensemaking’s tensions, scholars proposed different perspectives.

Theorists of cognitive distance argue that not too much distance in perspective is suitable for innovation (Nooteboom et al., 2007; Bergendahl & Magnusson, 2015). Differently, scholars from paradox theory (Lewis, 2000) explain that paradoxical perspectives foster collaboration. Still, empirical evidence is missing.

Research Questions

We explore how different level of distance in perspective affect the collaborative sensemaking people perform when developing shared innovative visions.

By focusing on the purest form of collaboration, the pair, we explore what happens when people work respectively with a partner they chose and with someone they would not choose.


In a context of action research, we run empirical tests in both B2B and B2C companies of different industries, during real project settings where our main intention was to support the company to envision and develop innovative directions.

As other scholars already explored (Weber, 2006; Frey, Goldstone 2016), the people involved were asked to move from individual ideation to pair ideation before to enter a larger team in defining the final direction. To have different levels of cognitive distance, people have been guided in the creation of both pairs and teams.

Empirical Material

Comprehensively, we involved 9 companies from different industries, for a total of 166 people. The people involved were top managers reporting directly to the company's CEO from different business units: they all are strictly connected with company strategy development and more accustomed to performing an intersubjective collaborative sensemaking process.

To assess the collaborative sensemaking process, a self-reported quantitative metric has been developed based on what scholars of the field already unearth (Duffy et al. 2013). In particular, we assessed participants' self-perception of meaningfulness through time both after pairs' and teams' phases in a thoughtful way (Weick, 1995).

We also assessed a few context variables that could affect meaningfulness. We assessed individuals' confidence with both the process (individual-pair-team) and the brief (innovation challenge) proposed. Finally, we assessed the individual energy level (personal status) on the workshop days.


In our investigation, we found that, when working in pair, individuals’ perception of vision’s meaningfulness grows significantly when they work with both someone very close and someone very separate in terms of cognitive distance. Indeed, when individuals work with someone they would not choose, hence with the highest level of cognitive distance, they activate those paradox frames that enable people to recognize contradictions and to build on these contradictions developing something innovative.

So far, scholars demonstrated how high level of cognitive distance negatively affect mutual understanding (Nooteboom, 2000) and brings to conflicts that cause a watering down of the vision’s meaningfulness (Van de Ven 1986; Tuckman 1965). In this paper, we build on what other scholars already unveiled about the positive relation between paradoxical frames and innovation (Miron-Spector et al. 2011; Andriopoulos et al., 2018). Indeed, when an individual works with a partner he/she did not even consider before, he/she approach the activity not in a conflicting mood (as would happen with other perceived consciously as different or not attractive). On the contrary he/she is more open to accept the contradictions perceived in the situation and to build on them to discover and learn something new.

Contribution to Scholarship

With this study, we aim to contribute to innovation literature by providing new perspectives on the study of collaboration in innovation and how it enables the development of breakthrough vision that are both shared and believed.

In particular, at first, we provide insights on collaboration by focusing on the purest form of collaboration possible, the pair. Indeed, although pair relationships in entrepreneurship are widely recognized (Jobs & Wozniak, for Apple, Page & Brin, for Google, Spiegel & Murphy, for Snapchat), they have been poorly explored with regard to innovation processes among consolidated companies (Hunter, 2012). Second, we provide a new perspective on deepening the nature of collaboration in innovation by leveraging on theories like cognitive distances and paradoxical frames.

Contribution to Practice

On a practical perspective, we provide managers a more profound understanding about which are the dynamics among people when collaborating in innovation with the aim to develop innovative shared directions. Moreover, we show how pairs can be a good intermediate step in the development of innovative directions: it facilitates the convergence towards a shared meaning which represents the essence of the innovation.


People engagement and convergence towards innovative and shared visions is one of the biggest challenges for companies: in a world overcrowded by ideas, the problem is not to have ideas but to identify the right breakthrough vision to pursue. Pair collaboration has the potentiality to help to solve this issue.


Andriopoulos, C., Gotsi, M., Lewis, M. W., & Ingram, A. E. (2018). Turning the sword: How NPD teams cope with Front‐End tensions. Journal of Product Innovation Management, 35(3), 427-445.

Bergendahl, M., & Magnusson, M. (2015). Creating ideas for innovation: Effects of organizational distance on knowledge creation processes. Creativity and Innovation Management, 24(1), 87-101.

Berger, P. L., & Luckman, T. (1966). Social construction of reality: A treatise in the sociology of knowledge. new york: Double day & company.

Cox, J. F., Pearce, C. L., & Perry, M. L. (2003). Toward a model of shared leadership and distributed influence in the innovation process: How shared leadership can enhance new product development team dynamics and effectiveness. Shared leadership: Reframing the hows and whys of leadership (pp. 48-76) SAGE Publications Inc.

Duffy, T., Baber, C., & Stanton, N. A. (2013). Measuring collaborative sensemaking. Iscram,

Eling, K., & Herstatt, C. (2017). Managing the front end of innovation—Less fuzzy, yet still not fully understood. Journal of Product Innovation Management, 34(6), 864-874.

Fellows, R., & Liu, A. (2016). Sensemaking in the cross-cultural contexts of projects. International Journal of Project Management, 34(2), 246-257.

Frey, S., & Goldstone, R. L. (2016). Does successful small-scale coordination help or hinder coordination at larger scales? Interaction Studies, 17(3), 371-389.

Goodman, N. (1978). Ways of worldmaking Hackett Publishing.

Hunter, S. T., Cushenbery, L. D., & Jayne, B. (2017). Why dual leaders will drive innovation: Resolving the exploration and exploitation dilemma with a conservation of resources solution. Journal of Organizational Behavior, 38(8), 1183-1195.

Hunter, S. T., Cushenbery, L., Fairchild, J., & Boatman, J. (2012). Partnerships in leading for innovation: A dyadic model of collective leadership. Industrial and Organizational Psychology, 5(4), 424-428.

Kijkuit, B., & Van Den Ende, J. (2007). The organizational life of an idea: Integrating social network, creativity and decision‐making perspectives. Journal of Management Studies, 44(6), 863-882.

Lewis, M. W. (2000). Exploring paradox: Toward a more comprehensive guide. Academy of Management Review, 25(4), 760-776.

Miron-Spektor, E., Gino, F., & Argote, L. (2011). Paradoxical frames and creative sparks: Enhancing individual creativity through conflict and integration. Organizational Behavior and Human Decision Processes, 116(2), 229-240.

Nooteboom, B. (2000). Learning by interaction: Absorptive capacity, cognitive distance and governance. Journal of Management and Governance, 4(1-2), 69-92.

Nooteboom, B., Van Haverbeke, W., Duysters, G., Gilsing, V., & Van den Oord, A. (2007). Optimal cognitive distance and absorptive capacity. Research Policy, 36(7), 1016-1034.

O'Connor, G. C., & Veryzer, R. W. (2001). The nature of market visioning for technology‐based radical innovation. Journal of Product Innovation Management: AN INTERNATIONAL PUBLICATION OF THE PRODUCT DEVELOPMENT & MANAGEMENT ASSOCIATION, 18(4), 231-246.

Pearce, C. L., & Ensley, M. D. (2004). A reciprocal and longitudinal investigation of the innovation process: The central role of shared vision in product and process innovation teams (PPITs). Journal of Organizational Behavior, 25(2), 259-278.

Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63(6), 384.

Van de Ven, Andrew H. (1986). Central problems in the management of innovation. Management Science, 32(5), 590-607.

Verganti, R. (2017). Overcrowded: Designing meaningful products in a world awash with ideas MIT Press.

Weber, R. A. (2006). Managing growth to achieve efficient coordination in large groups. American Economic Review, 96(1), 114-126.

Weick, K. E. (1995). Sensemaking in organizations (foundations for organizational science). Thousands Oaks: Sage Publications Inc,

Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409-421.

Weick, K. E., & Westley, F. (1999). Organizational learning: Affirming an oxymoron. Managing Organizations: Current Issues, 190-208.

Wenger, E. C., & Snyder, W. M. (2000). Communities of practice: The organizational frontier. Harvard Business Review, 78(1), 139-146.