Revisit: Decision Making and Positive Heuristics
New Challenges for Business Actors, Special issue of Management Decision; Deadline 30 Sep 2019
New challenges for business actors decision making and positive heuristics
Special issue call for papers from Management Decision
The most recent information about this call can be found at
Aim and Scope
This special issue focuses on the use of heuristics and forms of judgment based on simple rules by business actors in contexts characterized by increasing availability of information technologies (big data, artificial intelligence, marketing automation tools, etc.), and at the same time growing uncertainty.
Business actors include entrepreneurs, managers and entire organizations. Theories of entrepreneurship and management tend to focus on either the capabilities of the individual or the resources of the organization. Thus, these theories are incomplete to the extent that, as Herbert Simon and James March argued, success comes from the match between the individual and the organization.
Decision making is a relevant topic in the field of management and entrepreneurship. Managerial decision-making in the strategic -and especially entrepreneurial- context is characterized by a high degree of uncertainty regarding future developments of predominantly complex systems. To understand how individuals make decisions under uncertainty is a key question (Hammond 1996).
There are different research approaches to better understand decision-making under uncertainty and to develop models that better explain real-world decision-making processes and lead to improved theories and recommendations. For instance, intuition, sometimes defined as “choices made without obvious formal analysis” (Behling & Eckel, 1991: 47) has lost its flaw as being always inferior. Yet, there is neither a clear definition of intuition especially a clear delineation between gut feeling (without experience) and expert’s intuition (based on past experiences) nor a systematization of related concepts and terminologies such as positive, rational heuristics (Bingham & Eisenhardt, 2011), negative heuristics or decision-making biases (e.g., Kahneman 2011, Tversky & Kahneman 1974, Thaler, 1994), affective rationality and affective heuristics as well as the differentiation of experiential and analytic system as the two generic ways of human perception, judgment and decision-making (Slovic, et al., 2004) or the different forms and visions of rationality that include fast and frugal heuristics as a sub-category of bounded rationality (Gigerenzer & Todd, 1999).
While cognitive biases point towards the negative side of non-analytical decision making, positive heuristics express the view that simply rules can be more effective or the only feasible option in given situations for making appropriate decisions, considering their effectiveness beyond ideological prejudices. (Gigerenzer & Marewski, 2015).
Methods that are effective for analysing data insights are not the same for analyzing data foresight, because of the task environment. The research has to consider the conditions under which entrepreneurs and managers are more effective when they rely on intuition (see Bird 1988, or before Gragg 1940) and the conditions under which they are more effective when they rely on analysis (see Segars and Grover 1998, or before Knight 1921), or how other factors such as experience are related to intuitive decision making (Dane 2011). The research examining the decision-making processes adopted by the managerial experts confirms the diffusion and perception of effectiveness of decision-making methods based on heuristic rules (Maidique 2011, Guercini et al. 2015).
One could argue that technology increasingly makes available a great deal of information for economic actors, as well as a great ability to compute and to synthesize data in analytics (big data mangement). This makes it possible to tackle many problems, but it makes clear the need to adapt large data availability to people’s capabilities given their cognitive limits.
Given the role of increasing data availability, the question arises what role heuristics still play in managerial decision making (Artinger et al. 2015).
In this special issue, we propose to bring together experts in theories of individual judgment who also have experience and interest in entrepreneurship and management, with experts on entrepreneurship and management who also have experience and interest in individual judgment.
Topics for this special issue may include (but are not limited to):
- Examples of heuristics, simple rules and adaptive toolboxes used in specific business cases and contexts (industries, local systems etc.)
- Simple rules uses in specific decision making processes (entry in international markets; innovation processes etc.)
- Theory about rule based decision making in relation to wisdom in management; cognitive dimensions of framing; individual and collective cognition
- Scope of adoption and effectiveness of heuristics adopted by business actors in relation to context variables and action.
- Delineating heuristics from other forms of bounded rational decision making and its impact on organizations.
This special issue aims to provide high-quality, cutting edge research regarding heuristics in business actors’ decision making. This special call for papers for Management Decision
seeks theoretical and practical research avenues, frameworks, drivers, barriers, and best practices on the topic.
Papers should be submitted via the journal’s online submission system available through the journal homepage
When submitting please choose the special issue: “New challenges for business actors decision making and positive heuristics” as the article type from the drop down menu.
All papers must follow the guidelines outlined by the journal for submission, available at:
For any questions interested authors can contact the guest editor
Manuscript submission deadline: September 30, 2019
- Simone Guercini (University of Florence) email@example.com
- Christian Lechner (Free University of Bozen-Bolzano) firstname.lastname@example.org
Artinger, F., Petersen, M., Gigerenzer, G., & Weibler, J. (2015). Heuristics as adaptive decision strategies in management. Journal of Organizational Behavior, 36(S1), S33-S52.
Behling, O. & Eckel, N.L. (1991): Making sense out of intuition. Academy of Management Executive, 5(1), 46-54.
Bingham, C.B., Eisenhardt, K.M. (2011) Rational heuristics. The ‘simple rules’ that strategists learn from process experience, Strategic Management Journal, 32, 1437-1464.
Bird, B. (1988), Implementing entrepreneurial ideas: the case of intention, Academy of Management Review, 13(3), 442-453.
Dane, E. (2010): Reconsidering the trade off between expertise and flexibility: a cognitive entrenchment perspective, Academy of Management Review, 35, 579-603.
Gigerenzer, G., & Marewski, J. N. (2015). Surrogate science: The idol of a universal method for scientific inference. Journal of Management, 41(2), 421-440.
Gigerenzer, G. & Todd, P.M. (1999). Fast and frugal heuristics: The adaptive toolbox. In: Gigerenzer, G., Todd, P.M. & the ABC Research Group (Eds.), Simple heuristics that make us smart. Oxford University Press, Inc, New York: 3–34.
Gragg, C.I. (1940), Because wisdom can’t be told, Harvard Alumni Bulletin, October, Cambridge Mass.
Guercini, S., La Rocca, A., Runfola, A., & Snehota, I. (2015). Heuristics in customer-supplier interaction. Industrial Marketing Management, 48, 26-37.
Knight, F. (1921), Risk, uncertainty and profit, State University of Iowa, Iowa City.
Maidique, M.A. (2011), The leader’s toolbox, working paper, Florida International University.
Segars, A.H., and Grover, V. (1998), Strategic information systems planning success: an investigation of the construct and its measurement, MIS Quarterly, 22(2), 139-163.
Slovic, P., Finucane, M., Peters, E. & MacGregor, D. (2004). Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24(2), 311–322.
Thaler, R. H. (1994). Quasi rational economics. Russell Sage Foundation.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.