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Strong versions of the Precautionary Principle (PP) require regulators to prohibit or impose technology controls on activities that pose uncertain risks of possibly significant environmental harm. This decision rule is conceptually unsound and would diminish social welfare. Uncertainty as such does not justify regulatory precaution. While they should reject PP, regulators should take appropriate account of societal aversion to risks of large harm and the value of obtaining additional information before allowing environmentally risky activities to proceed.

This paper aims to introduce eristic decision-making in entrepreneurship. A decision is eristically made when it utilizes eristics, which are action-triggering short-cuts that draw on hedonic urges (e.g. sensation-seeking). Unlike heuristics, eristic decision-making is not intendedly rational as eristics lead to decision-making without calculating or even considering the consequences of actions. Eristics are adaptive when uncertainty is extreme. Completely novel strategies, nascent venturing, corporate venturing for radical innovation and adapting to shocks (e.g. pandemic) are typically subject to extreme uncertainties.

In light of the relevant debates in entrepreneurship, psychology and decision sciences, the paper builds new conceptual links to establish its theoretical claims through secondary research.

The paper posits that people adapt to extreme uncertainty by using eristic reasoning rather than heuristic reasoning. Heuristic reasoning allows boundedly rational decision-makers to use qualitative cues to estimate the consequences of actions and to make reasoned decisions. By contrast, eristic reasoning ignores realistic calculations and considerations about the future consequences of actions and produces decisions guided by hedonic urges.

Current entrepreneurial research on uncertainty usually focuses on moderate levels of uncertainty where heuristics and other intendedly rational decision-making approaches pay off. By contrast, this paper focuses on extreme uncertainty where eristics are adaptive. While not intendedly rational, the adaptiveness of eristic reasoning offers theoretically and psychologically grounded new explanations about action under extreme uncertainty.

The purpose of this paper is to explore the concept of “common sense” and to distinguish it from uncommon sense as it applies to managerial decision‐making under conditions of task uncertainty. The paper enunciates the definition of common sense decision‐making and develops the concept of “uncommon” sense making. A typology of common sense is put forth, and a case study is used to illustrate it in practice.

This is a conceptually developmental paper, which explores and develops the concept of uncommon sense through literature review and typology development. A mechanistic, or internally driven, decision approach is compared with an organic, externally driven one, and the question of how common sense is related to these approaches in varying task uncertainty conditions is explored. A short case study is used as an illustration of the practical managerial implications under low task certainty conditions.

The concepts of MCS (common sense) and MUS (uncommon sense) are established, as well as O and M errors. It is suggested that within a mechanistic approach MCS is most appropriate in conditions of high task certainty. Within an organic approach MUS is most appropriate in conditions of low task certainty. An O error occurs when a mechanistic approach is taken, using common sense, under low task certainty. Lack of appropriate resources deems such an approach unsuitable. An M error occurs when a more risky organic approach (MUS) is taken when resources exist to make a common sense decision.

Increasing globalization, work ambiguity, and task complexity, introduce a need for greater managerial adaptability and speed. MUS may therefore play an increasingly greater role in organizational decision‐making as managers seek answers to questions generated by new and unique situations where existing decision rules may not apply.

The theoretical framework offered in this paper looks at the increasingly common situations in which “thinking outside the box” is essential for sound decision making. It suggests a taxonomy that allows for exploration as well as application of “uncommon sense”‐based theory in situations that require such innovative thinking. It takes a significant step in the theoretical and practical understanding of the very relevant issues of inspiration, adventure and creativity in managerial decision making today.

In recent years Professor Shackle's numerous, highly imaginative and original works on the role of expectation and uncertainty in the modelling of economic behaviour have at last become more widely acknowledged. However, still relatively little attention is paid to one of his seminal and earliest studies, that concerned with his own theory of expectations and individual decision making under uncertainty, work on which was begun and published in the 1930s and completed in 1949 with the appearance of the first edition of Expectation in Economics. Thereafter, until the early 1960s, his theory received a modest amount of interest. However, it tended to become neglected; reference rarely appears to it in books or papers on expectation, even in those papers discussing decision making under uncertainty (see, as one of the latest examples, G. O. Schneller and G. P. Sphicas, 1983). The literature has been dominated by the risk‐based, expected utility approach to decision taking.

Really new products (RNP) run the risk not only of technical problems in the development process, but also of problems with customer acceptance. Because market uncertainty in particular is frequently high, many top management teams defer essential management decisions on these products until sufficient information is available to be able to make a sound decision. In many cases, however, the market is already been divided up by that time. The purpose of this paper is to examine how better information about customers can be acquired by providing them with a better offering of information which has been prepared in a variety of forms (“information acceleration”) and how management decisions can be improved as a result.

The paper is based on modern models for decision making under uncertainty that incorporate group decisions, and shows how the measurement of purchasing behavior can be improved by information acceleration in a test studio. This is needed because customers generally cannot draw on mentally established analogies in the case of RNP, so that they are virtually unable to make meaningful statements that would improve strategic management decisions when completing standard customer surveys. A test studio was set up in the form of a Car Clinic for the example of a future electric vehicle as a RNP. 121 customers were to be offered a wide variety of information (about the future urban environment, the design of the vehicle concept and the driver’s experience), partly in order to acquire information about the customers. In particular, the extent to which customers could better evaluate their purchasing probability and willingness to pay certain prices and the extent to which the variance of customer opinions was reduced after attending the Car Clinic were examined, because these factors make it easier to forecast future sales revenue and management decisions can be made more easily.

The results reveal that information acceleration in a test studio can improve the estimation of sales revenue in an early decision-making phase and can have a positive influence on decision-making behavior under uncertainty.

This study provides an empirical, valuable step toward an investigation of management decisions on RNP under uncertainty.

Travel behaviour depends on the travellers' perception of the trip characteristics. The uncertainty of the journey time is one of the determinants of the choice. Studies of decision behaviour in uncertain conditions show the limited validity of the common assumptions in traffic models. Decision making under uncertainty has to be considered as a contingent process, depending on the objectives and conditions with which the choice is made. Expected utility is one of the many possible criteria used by people to decide. There is a discrepancy between the objective and subjective value of this concept. This is due to the bias with respect to the perception of very likely and very unlikely events. In many cases the expected utility is a less applicable objective, e.g. because people want to arrive before a certain deadline and maximize the probability to achieve that. The fact that probabilities of travel times have to be learned from experiences introduces a dynamic character of choice behaviour.

Most of the reported properties of decision-making under uncertainty still have to be verified for travel behaviour.

Commercial property development builds floor space in anticipation of potential, but unknown, future demand, making it particularly prone to risk and uncertainty. The research explores the degree to which property developer decision-making is objective and rational and the degree to which it relies on behavioural instincts and intuition. Decision-making theory, including heuristics, is considered and its prevalence in the field of commercial property development is examined.

A “dual-processing” decision-making model, comprising intuitive System 1 and objective System 2 processing, is proposed and tested. Inductive research using template analysis of interviews, with “high status” commercial property developers, explored whether the model offers an accurate representation of developers' behaviour and effective lens through which to examine decisions made under conditions of risk and uncertainty.

Participants believed they adopted objective and rational approaches to complex commercial property development decisions. Analysis of interviews reveals that System 1 heuristics and intuition play significant roles in decision-making behaviour, leading to potential bias and systematic error. The research concludes that the dual-processing model provides a useful lens through which to better understand the decision-making approach adopted by commercial property developers.

The research represents the rare application of behavioural theory to the realm of commercial property development and provides new and original insight as to how important investment decisions are made under conditions of risk and uncertainty, with implications for professional practice.

This study aims to examine individuals' tendency to strictly follow their own signal while ignoring predecessors' decisions when making decisions under varying degrees of uncertainty.

Using a controlled laboratory experiment, the authors separate the follow-own-signal behavior from other types of behavior such as Bayes consistent or herd-like (i.e. follow-the-majority) behavior.

As the authors systemically increase the degree of uncertainty in the information environment, participants are increasingly more likely to act only on their own signal. This suggests that financial decisions that are made under highly uncertain market conditions may be more signal revealing, and hence, may lead to better information aggregation than previously thought. The authors also find that as uncertainty increases, participants are more likely to switch in and out of this behavior, suggesting that behavior under highly uncertain conditions may also be more random and complex.

The authors are the first to examine how uncertainty affects the follow-own-signal behavior. The authors also offer potential testable empirical implications, such as an increase in contrarian investing, home bias, and own-company ownership under times of increased uncertainty or in more uncertain markets.

The appropriate use of decision strategies can be of marked benefit to effective decision making. The challenge of decision making under uncertain conditions and the absolute necessity of decision aids for the practising manager at nearly any level of the organisation are examined. Specific strategies are developed for making effective decisions based on the amount of information available and the degree of environmental uncertainty and a framework for selecting the correct strategy put forward, since these strategies are only appropriate given certain conditions.

The paper introduces a new model, the evolutionary-existential model of organizational decision-making. The purpose of the model is to provide an empirical framework for understanding the context for decision-making under conditions of existential threat to organizations, such as the global COVID-19 pandemic during the year 2020.

The model is built on an extensive interdisciplinary literature review, drawing from research in social psychology, management, behavioral economics, evolutionary psychology and consumer behavior. In general, the authors follow Bargal's (2006) call for action research in the spirit of Lewin (1951).

According to the model, organizational decision-making during the pandemic threat is influenced by (1) existential threat and (2) an unprecedented macroenvironmental context for decision-making. The authors argue that these psychological and macroenvironmental forces may lead to suboptimal decision-making, based on (1) their basic cognitive architecture and (2) specific evolutionary triggers activated by the pandemic. The authors highlight how the interaction between these inputs and the decision context manifest in various social psychological phenomena that are known to impact judgments and decisions.

Simply put, the magnitude and the urgency of the global pandemic call for new and integrative ways of understanding organizational decision-making.

The model is new. Although the authors draw on prior research and theory, the model is uniquely interdisciplinary; further, the authors are able to make specific and unique predictions about the inputs, decision context and their social–psychological consequences for decision-making.