Entrepreneurial Cognition

by Dean A Shepherd

  Metacognitive Experience

  Metacognitive experience refers to experiences that are affective, are based on cognitive activity, and serve as a channel through which prior experiences, memories, intuitions, and emotions may be used as resources in the process of making sense of a specific task , problem, or situation (Flavell 1979). For instance, an individual has a metacognitive experience if he or she feels that a specific task is challenging to undertake or understand. In the next step, he or she draws on that prior experience to yield the creation of a new decision framework for a new but similar task . Like past experiences, emotions and intuitions related to prior situations can shape the generation of decision frameworks for novel tasks . As an example, emotions like fear, anger, joy, or grief or that are connected to an event in the past may serve to influence—at a metacognitive level—the development of future decision frameworks aimed at novel events, tasks , or situations similar to those from which the experienced emotions stemmed. Intuitions serve a similar function in the metacognitive creation of decision frameworks: if the individual tends to draw on intuitions resulting from prior experiences, those intuitions will likely influence the development of future decision frameworks aimed at new tasks , events, or situations. A manager, for instance, may draw a decision based on a “hunch,” which reflects his or her reliance on intuition (Miller and Ireland 2005). In simple terms, metacognitive experiences enable people to make sense of their social world more easily (Earley and Ang 2003) and thus, together with metacognitive knowledge , help individuals choose a decision framework. Therefore, my (Dean) colleague and I (Haynie and Shepherd 2009: 697) referred to metacognitive knowledge as the degree to which the individual depends on idiosyncratic experiences, emotions , and intuitions when generating multiple decision frameworks aimed at interpreting, planning, and implementing goals to “manage” a changing environment.

  Metacognitive Choice

  Thus, individuals select and use a particular decision framework (chosen among the set of available alternatives) in the context of their goal orientation to plan and implement objectives to “manage” dynamic environments. This selection among numerous decision frameworks is similar to a golfer choosing a particular club based on his or her goals for a specific shot. Each club in the golfer’s bag can be seen as an alternative path to action and goal realization—getting the ball to the green and into the hole. Yet, depending on the nature of the specific shot at hand (e.g., in a sand trap versus on the fairway), there is a “most suitable” club for that shot—namely, the club that will help the golfer realize his or her goal. An individual who is cognitively adaptable and draws on his or her metacognitive knowledge and experience generates various alternative decision frameworks as possibilities (different clubs) to interpret an altered reality and then chooses the most suitable option from that set of possibilities in light of his or her goals to most effectively reach that goal. Thus, my (Dean) colleague and I (Haynie and Shepherd 2009: 700) defined metacognitive choice as the degree to which the individual engages in the active process of choosing the most suitable option among multiple decision frameworks that helps him or her best interpret, plan, and implement a response in order to “manage” a changing environment.

  Monitoring

  Implementing the chosen decision framework will result in action that generates feedback to additional adaptive cognitions (Flavell 1979). According to Flavell (1979), the purpose of a metacognitive strategy is to feel confident that the goal has been accomplished. In line with Flavell’s proposition, metacognition has mechanisms to evaluate the result of implementing a specific decision framework in relation to one’s goal orientation , metacognitive knowledge , and metacognitive experience (Flavell 1979). Monitoring a person’s own cognitions happens both during and after the process of interpreting, planning, and implementing a response to an altered reality. Depending on the particular characteristics of the association between current performance and a person’s goal orientation , monitoring this relationship may prompt him or her to reassess their motivation (Locke et al. 1984; Locke and Latham 1990; Nelson and Narens 1994) and/or his or her metacognitive knowledge , metacognitive experience , and/or the particular decision framework chosen based on the setting at hand (i.e., metacognitive choice). As such, monitoring refers to looking for and utilizing feedback to reassess one’s goal orientation , metacognitive knowledge, metacognitive experience, and metacognitive choice in order to “manage” a changing environment (Haynie and Shepherd 2009: 700).

  Learning to Think Metacognitively

  Over the past decade, researchers have explored various instructional approaches that harness metacognition to improve reasoning (Kramarski et al. 2001). Mevarech and Kramarski (1997) created an instructional method to help students enhance their mathematical reasoning by developing their metacognitive skills through four types of questions based on (1) comprehension, (2) connection, (3) strategy, and (4) reflection (Mevarech and Kramarski 2003: 469). We refer to these questions as “metacognitive questions” as they are used to stimulate learners’ metacognition.

  First, comprehension questions are intended to encourage one to think about whether he or she really understands the nature of a particular problem before starting to address it. This understanding forms from carefully considering the situation such that one identifies a problem, its nature , and its implications. The following are examples of questions encouraging students to think about comprehension: What is the core of the problem? What is the key question asked? What meanings do the key concepts convey?

  Second, connection questions are intended to encourage students to think about a particular problem in terms of its similarities and differences with problems he or she has faced and solved before. These questions urge students to draw on existing knowledge and experiences without generalizing from them too much. Questions like the following prompt learners to think about these connections: How can I relate this problem to problems I addressed previously? In what ways does this problem differ from those I worked on in the past, and how does it differ?

  Third, strategic questions are intended to encourage students to think about which strategies are most suitable for solving a problem and why. These questions urge learners to contemplate the what, why, and how underlying their approach to a problem. The following are examples of strategic questions: What is the strategy/tactic/principle best suited for me to address this problem? Why is this strategy/tactic/principle so particularly appropriate? How can I put together information I need for solving the problem? How can I realize the plan?

  Fourth, reflection questions are intended to encourage students to think about their understanding and feelings as they progress through the problem-solving process. These tasks help students generate their own feedback (i.e., develop a feedback loop in their solution process) to provide the chance to change. Examples of reflection questions include the following: What am I doing? It there any sense in what I am doing? Are there particular challenges I have to address? How do I feel about it? In what way can I verify the proposed solution to the problem? Is it possible to draw on a different approach to tackle this task ?

  Metacognitive training helps decision makers (1) develop and answer a set of self-addressed questions that are in line with those described above (Kramarski et al. 2002); (2) clarify why it is important to ask and answer these types of questions (Kramarski and Zeichner 2001); and (3) utilize these questions when contemplating or reflecting on new ideas (Kramarski et al. 2002), such as potential opportunities. A significant number of empirical studies have found that metacognitive skills (as represented by asking and answering the questions outlined above) enable learning (e.g., Kramarski and Zeichner 2001; Mevarech and Kramarski 2003). Overall, these questions prompt people to think about their learning , which can positively affect their subsequent task performance. For instance, metacognitive training improves individuals’ (1) adaptability to new situations (i.e., it provides a foundation on which an individual’s prior knowle
dge and experience influence his or her learning or problem-solving in a novel situation (Mayer and Wittrock 1996: 48)), (2) creativity (i.e., it can result in unique and flexible solutions, ideas, or perceptions (Runco and Chand 1995)), and (3) communication of the thinking underlying a specific response (Mevarech and Kramarski 2003). Each of these skills is very valuable for entrepreneurs.

  Conclusion

  Managers’ attention is a limited resource, and where they allocate attention influences several aspects of the entrepreneurial process, including environmental changes and the recognition , evaluation, and exploitation of opportunities. Research has uncovered several factors at the individual, organizational, and environmental level that explain how entrepreneurs allocate attention. In this chapter, we illustrated that cognitive processes, particularly metacognition , impact individuals’ attention allocation and thereby entrepreneurial outcomes. We now turn to the topic of entrepreneurial identity , which has attracted considerable scholarly interest over the last several years.

  Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

  The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

  References

  Aldrich, H. E. (1979). Organizations and environments. Englewood Cliffs: Prentice-Hall, 16(2), 183–214.

  Allen, B. A., & Armour-Thomas, E. (1993). Construct validation of metacognition. The Journal of Psychology, 127(2), 203–211.

  Ariely, D., & Carmon, Z. (2000). Gestalt characteristics of experiences: The defining features of summarized events. Journal of Behavioral Decision Making, 13(2), 191–201.

  Ariely, D., & Zauberman, G. (2000). On the making of an experience: The effects of breaking and combining experiences on their overall evaluation. Journal of Behavioral Decision Making, 13(2), 219.

  Bakker, R. M., & Shepherd, D. A. (2017). Pull the plug or take the plunge: Multiple opportunities and the speed of venturing decisions in the Australian mining industry. Academy of Management Journal, 60(1), 130–155.

  Baum, J., & Wally, S. (2003). Strategic decision speed and firm performance. Strategic Management Journal, 24(11), 1107–1129.

  Behrens, J., & Patzelt, H. (2016). Corporate entrepreneurship managers’ project terminations: Integrating portfolio-level, individual-level, and firm-level effects. Entrepreneurship Theory and Practice, 40(4), 815–842.

  Behrens, J., Ernst, H., & Shepherd, D. A. (2014). The decision to exploit an R&D project: Divergent thinking across middle and senior managers. Journal of Product Innovation Management, 31(1), 144–158.

  Beyer, J. M., Chattopadhyay, P., George, E., Glick, W. H., & Pugliese, D. (1997). The selective perception of managers revisited. Academy of Management Journal, 40(3), 716–737.

  Bingham, C. B., & Eisenhardt, K. M. (2011). Rational heuristics: The ‘simple rules’ that strategists learn from process experience. Strategic Management Journal, 32(13), 1437–1464.

  Bogner, W. C., & Barr, P. S. (2000). Making sense in hypercompetitive environments: A cognitive explanation for the persistence of high velocity competition. Organization Science, 11(2), 212–226.

  Bourgeois, L. J., III, & Eisenhardt, K. M. (1988). Strategic decision processes in high velocity environments: Four cases in the microcomputer industry. Management Science, 34(7), 816–835.

  Bowman, E. H., & Hurry, D. (1993). Strategy through the option lens: An integrated view of resource investments and the incremental-choice process. Academy of Management Review, 18(4), 760–782.

  Brown, S. L., & Eisenhardt, K. M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1–34.

  Budescu, D. V., & Yu, H.-T. (2007). Aggregation of opinions based on correlated cues and advisors. Journal of Behavioral Decision Making, 20(2), 153–177.

  Carpenter, M. A. (2002). The implications of strategy and social context for the relationship between top management team heterogeneity and firm performance. Strategic Management Journal, 23(3), 275–284.

  Castañer, X., & Kavadis, N. (2013). Does good governance prevent bad strategy? A study of corporate governance, financial diversification, and value creation by French corporations, 2000–2006. Strategic Management Journal, 34(7), 863–876.

  Cho, T. S., & Hambrick, D. C. (2006). Attention as the mediator between top management team characteristics and strategic change: The case of airline deregulation. Organization Science, 17(4), 453–469.

  Choi, Y. R., & Shepherd, D. A. (2004). Entrepreneurs’ decisions to exploit opportunities. Journal of Management, 30(3), 377–395.

  Choi, Y. R., Lévesque, M., & Shepherd, D. A. (2008). When should entrepreneurs expedite or delay opportunity exploitation? Journal of Business Venturing, 23(3), 333–355.

  Christensen, C. M. (1997). The innovator’s dilemma. Cambridge: Harvard Business School.

  Csaszar, F. A. (2013). An efficient frontier in organization design: Organizational structure as a determinant of exploration and exploitation. Organization Science, 24(4), 1083–1101.

  Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs: Prentice-Hall, 2, 15(3), 457–460.

  Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational action. Academy of Management Review, 12(1), 76–90.

  Earley, P. C., & Ang, S. (2003). Cultural intelligence: Individual interactions across cultures. Stanford: Stanford University Press.

  Eggers, J. P., & Kaplan, S. (2009). Cognition and renewal: Comparing CEO and organizational effects on incumbent adaptation to technical change. Organization Science, 20(2), 461–477.

  Einhorn, H. J., & Hogarth, R. M. (1985). Ambiguity and uncertainty in probabilistic inference. Psychological Review, 92(4), 433.

  Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal, 32(3), 543–576.

  Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10), 1105–1121.

  Eisenhardt, K. M., & Schoonhoven, C. B. (1990). Organizational growth: Linking founding team, strategy, environment, and growth among US semiconductor ventures, 1978–1988. Administrative Science Quarterly, 35(3), 504–529.

  Eisenhardt, K. M., Furr, N. R., & Bingham, C. B. (2010). Microfoundations of performance: Balancing efficiency and flexibility in dynamic environments. Organization Science, 21(6), 1263–1273.

  Finkelstein, S., & D’aveni, R. A. (1994). CEO duality as a double-edged sword: How boards of directors balance entrenchment avoidance and unity of command. Academy of Management Journal, 37(5), 1079–1108.

  Finkelstein, S., & Hambrick, D. C. (1990). Top-management-team tenure and organizational outcomes: The moderating role of managerial discretion. Administrative Science Quarterly, 35(3), 484–503.

  Fiske, S. T., & Taylor, S. E. (1991). McGraw-Hill series in social psychology. In Social cognition. New York: Mcgraw-Hill Book Company, 102(2), 246–268.

  Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906.

  Floyd, S. W., & Wooldridge, B. (1997). Middle management’s strategic influence and organizational performance. Journal of Management Studies, 34(3), 465–485.

  Forbes, D. P. (2005). Are
some entrepreneurs more overconfident than others? Journal of Business Venturing, 20(5), 623–640.

  Franconeri, S. L., & Simons, D. J. (2003). Moving and looming stimuli capture attention. Attention, Perception, & Psychophysics, 65(7), 999–1010.

  Franconeri, S. L., Hollingworth, A., & Simons, D. J. (2005). Do new objects capture attention? Psychological science, 16(4), 275–281.

  Frey, K. P., & Eagly, A. H. (1993). Vividness can undermine the persuasiveness of messages. Journal of Personality and Social Psychology, 65(1), 32.

  Gatignon, H., Tushman, M. L., Smith, W., & Anderson, P. (2002). A structural approach to assessing innovation: Construct development of innovation locus, type, and characteristics. Management Science, 48(9), 1103–1122.

  Gavetti, G., Levinthal, D., & Ocasio, W. (2007). Neo-Carnegie: The Carnegie school’s past, present, and reconstructing for the future. Organization Science, 18(3), 523–536.

  George, G. (2005). Slack resources and the performance of privately held firms. Academy of Management Journal, 48(4), 661–676.