User:JDinJD/Behavioral strategy

Reconstruction of the Behavioral Strategy Wikipedia Page:

Edit “Meaning” so it is not a heading and include the information as a continuation of the Behavioral Strategy definition.

After the “Lines of Study” information, we will include the “Major Historical Contributions” and then “Development”.

After “Defining the Field of Behavioral Strategy”, will be “Applying Behavioral Strategy to Extreme Circumstances such as Covid 19 and the Implications”. Then we can finish with the “Limitations of Behavioral Strategy”.

Lines of Study
Behavioural finance integrates psychological research that describes how people behave in real life and applies it to finance. This research resulted in the formation of two independent study lines:

The first is about how investor behavior may differ from the textbook definition of an efficient rational investor. The other is how investors who aren't completely rational can cause market prices to vary from their underlying values.

The first strand of research examines how investors act in order to determine how investing strategies should meet their desires. The second strand of research examines how investor behavior may influence market functioning; It's used to determine whether active investment managers will find it simpler to outperform (the short answer is "no").

In 2002, a professor of psychology, Daniel Kahneman, was awarded the Nobel Prize in Economics (who won it jointly with Vernon Smith) in recognition of the contribution that behavioral analysis is now making in financial economics. This research arose from a series of experiments that yielded significant findings about the biases that influence how people make decisions and create preferences.

Giving investing advice requires a thorough grasp of investor preferences, and understanding investor biases is crucial for predicting how investors will react to specific events or developments. If biases are flaws that could harm an investor's interests, investing advisers should avoid catering to them. This, for example, implies a need for investor education. Investors and their advisers should be aware of these biases because they will influence how they react to a variety of predicted market movements.

Justin:

Major Historical Contributions:
Herbert Simon's research on cognitive decision making and the concept of bounded rationality contributed to further research in decision making and behavioral strategy. Simon's research also led him to four categoric observations on variations in ability to solve complex problems and make decisions. (Cite)

Simons Observations:

These observations provided early support in the development of research on behavioral strategy.
 * 1) One key to solving problems lies within adequate representation of the problem. Those who show proficiency in solving problems, also represent the problem accurately, highlighting the nature of the problem and utilizing the most pertinent information necessary for a solution.
 * 2) Effective problem solvers use patterns. When analyzing problems and their solutions, patterns emerge. These patterns translate to 'if/then' solutions. Porter's five Forces model is an example of 'if/then' solutions with recurring patterns that consistently connect problems with effective solutions. If your supplier has high bargaining power, then seek alternative sources, as an example.
 * 3) Patterns increase memory encoding and recall. A connection to a memory allows faster recall from long term memory, and patterns increase this connection making memories easier to recall.
 * 4) Practice increases expertise. Practicing decision making and problem solving correlates to increased skill. Using representation, recognizing and remembering patterns, and recalling these patterns increases one's abilities.

Bre'anna:

Applying Behavioral Strategy to Extreme Circumstances such as Covid 19 and the Implications
Behavioral strategy affected decisions made during the COVID-19 disruption. Behavioral strategy provides psychologically based interpretations that can illuminate how individuals and organizations respond to such disruptions. It suggests that strategists may not be good at using formal models, rules, or forecasts because they are not statisticians. There is supporting evidence of this observed during the disruption caused by Covid-19. Some decision-makers treated extreme model projections as deterministic predictions rather than recognizing them as improbable worst-case scenarios. An example of this was the societal lockdown. It was impossible to forecast the economic and social consequences of the lockdown, and its effectiveness, and yet decision-makers decided to implement this worst-case scenario. Another example of worst-case scenario being implemented is when the CDC gave guidance on wearing masks outdoors as this was an example of extreme caution. Decision-makers appeared to overlook the consequences of or misunderstand the lack of error margins around initial forecasts. Also of relevance, decision-makers may rely too much on models, forecasts, and data that are available. When decision-making problems are ill-structured and require quick action, relying solely on formal models and forecasts can be problematic. It becomes necessary to incorporate intuition and soft data into the decision-making process in these cases. (Foss, 2020)

Limitations of Behavioral Strategy
Strategy making is a deeply social process and strategy research doesn't sufficiently account for this. Different experts' social standards vary, and this will influence what information is collected. COVID-19 highlighted how behavioral strategy frameworks don’t allow dealing with uncertainty beyond standard treatments of risky decision-making. Behavioral strategy is useful in extreme circumstances, however, there is more research to be done on the weaknesses present for disruptions like this.

Ivis:

Behavioral strategy has developed gradually into a significant subfield within strategic management. It applies insights from social psychology and cognitive to intensify strategic decision-making by understanding social dynamics and human cognition. Behavioral strategy focuses on top managers’ cognitive processes and emphasizes collaboration and communication patterns. The foundation lies in the behavioral decision theory.

Strategic cognition delves into understanding the cognitive structures within organization and the decision-making processes. Effective and intuitive reasoning plays a significant role in strategy formulation, it comes to influence organizational and managerial cognition.

The field of Behavioral strategy has gained significant attention in academic circles, with issues and volumes dedicated to it in prestigious conferences and publications. The field remains scattered and diverse despite its growth. To address this issue scholars propose integrating theoretical and empirical attention. This integration aims to provide more understanding of how behavior can impact strategic outcomes.

(The study undertakes citation-based systematic literature review to provide a better understanding of behavioral strategy. It addresses the lack of reviews in literature, it aims to illuminate the key sources, contributors, and contribution in the field. Through network analysis and bibliometric, paper maps the network of authors, documents, growth patterns, influential articles, and intellectual structure of behavioral strategy. It identifies and suggests path for future research, it will serve as a valuable resource for researchers that are interested in this area.)

References:
Anwar, Jamil, Aqsa Bibi, and Nisar Ahmad. “Behavioral Strategy: Mapping the Trends, Sources and Intellectual Evolution.” Journal of Strategy and Management 15.1 (2022): 140–168. https://www.emerald.com/insight/content/doi/10.1108/JSMA-01-2021-0002/full/html

Schrager, J.E. and Madansky, A. (2013), "Behavioral strategy: a foundational view", Journal of Strategy and Management, Vol. 6 No. 1, pp. 81-95. https://doi.org/10.1108/17554251311296576

Simon, H.A. (1976), "The information storage system called 'human memory'", in Rosenzweig, M.R. and Bennett, E.L. (Eds), Neural Mechanisms of Learning and Memory, MIT Press, Cambridge, MA, pp. 79-96.