Making Strategic Decisions Under Time Pressure - A Process-based Analysis Approach
Translated title
Strategisches Entscheidungsverhalten unter Zeitdruck - ein Prozess-basierter Analyseansatz
Publication date
2024-03
Document type
PhD thesis (dissertation)
Author
Kremer, Marco
Advisor
Tüshaus, Ulrich
Referee
Granting institution
Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg
Exam date
2024-02-27
Organisational unit
Part of the university bibliography
✅
DDC Class
330 Wirtschaft
Keyword
time pressure
normal-form games
elementary information processes
mouse tracking
process tracing
behavioral decision-making
data clustering
behavior types
heuristics
Abstract
Although many strategic economic decisions are subject to time constraints, the impact of time pressure on the decision-making process of solving non-cooperative games has not been well studied in the field of behavioral game theory. This includes the effects of time pressure on decision-making in non-cooperative games (Ariely and Zakay, 2001; Ordóñez et al., 2015). Lindner and Sutter (2013) conducted the first study investigating personal sophistication in terms of the cognitive hierarchy model. To experimentally determine the distribution of level-k-reasoning types, they utilized Arad & Rubinstein’s (2012) 11-20-Game. Contrary to the findings of Sutter et al. (2003) and Kocher et al. (2006), the authors discovered a shift towards equilibrium play under growing time pressure. They attribute this discrepancy to chance since the decision information is the only factor available for interpretation.
Applying a process-oriented approach in combination with process tracing methods provides valuable insights into people's decision-making behavior (Kühberger et al., 2011). In normal-form games with no time pressure, Costa-Gomes et al. (2001) found evidence of the application of common decision heuristics by scrutinizing lookup patterns in information search, response time, and decision information. However, the use of heuristics may not be stable or complete under time-pressure conditions (Johnson et al., 2008). This raises the question of what more detailed behavior patterns might be identifiable and how such patterns change with increasing time pressure.
Therefore, this work develops a process theoretical framework called the 'Preparation Time Model'. This framework bases decision-making on Elementary Information Processes (EIPs) following Johnson and Payne (1985) and Chase (1978). Production systems for solving normal-form games are constructed for nine common heuristics based on EIPs (following suggestions of Newell et al., 1972). A minimum set of EIPs and how it can be identified in mouse tracking data is derived. The effectiveness and efficiency of heuristics in different games and under various time pressure conditions are determined through simulation. Significant differences in adaptation velocity between strategic and non-strategic heuristics raise the question of the extent to which it is rational to employ certain strategic heuristics under severe time pressure conditions.
This work also reports on an online experiment that was conducted using Mouselabweb (Willemsen and Johnson, 2011) to investigate the influence of time constraints and task complexity on individual decision-making and its patterns in 2-person normal form games. The empirical dataset was analyzed for fifteen behavior patterns from the process categories Information Search, Information Implementation, and Choice, which frequently show sensitivity to time pressure. Data clustering indicates the existence of different types of decision-makers who pursue individual strategies to deal with time pressure: the “Strategist”, the “Adaptist”, and the “Guesser”. The findings confirm the qualitative response schema of individuals acting under time pressure in individual decision situations, as described by Miller (1960), Ben Zur and Breznitz (1981), and Zakay (1993), and specify the schema for the case of normal-form game tasks. However, questions regarding the extent to which heuristics are applied or whether findings are robust for predicting behavior remain unanswered. The empirical dataset holds potential for further scrutiny.
Applying a process-oriented approach in combination with process tracing methods provides valuable insights into people's decision-making behavior (Kühberger et al., 2011). In normal-form games with no time pressure, Costa-Gomes et al. (2001) found evidence of the application of common decision heuristics by scrutinizing lookup patterns in information search, response time, and decision information. However, the use of heuristics may not be stable or complete under time-pressure conditions (Johnson et al., 2008). This raises the question of what more detailed behavior patterns might be identifiable and how such patterns change with increasing time pressure.
Therefore, this work develops a process theoretical framework called the 'Preparation Time Model'. This framework bases decision-making on Elementary Information Processes (EIPs) following Johnson and Payne (1985) and Chase (1978). Production systems for solving normal-form games are constructed for nine common heuristics based on EIPs (following suggestions of Newell et al., 1972). A minimum set of EIPs and how it can be identified in mouse tracking data is derived. The effectiveness and efficiency of heuristics in different games and under various time pressure conditions are determined through simulation. Significant differences in adaptation velocity between strategic and non-strategic heuristics raise the question of the extent to which it is rational to employ certain strategic heuristics under severe time pressure conditions.
This work also reports on an online experiment that was conducted using Mouselabweb (Willemsen and Johnson, 2011) to investigate the influence of time constraints and task complexity on individual decision-making and its patterns in 2-person normal form games. The empirical dataset was analyzed for fifteen behavior patterns from the process categories Information Search, Information Implementation, and Choice, which frequently show sensitivity to time pressure. Data clustering indicates the existence of different types of decision-makers who pursue individual strategies to deal with time pressure: the “Strategist”, the “Adaptist”, and the “Guesser”. The findings confirm the qualitative response schema of individuals acting under time pressure in individual decision situations, as described by Miller (1960), Ben Zur and Breznitz (1981), and Zakay (1993), and specify the schema for the case of normal-form game tasks. However, questions regarding the extent to which heuristics are applied or whether findings are robust for predicting behavior remain unanswered. The empirical dataset holds potential for further scrutiny.
Cite as
Kremer, Marco (2024): Making Strategic Decisions under Time Pressure. 1. Aufl. Hamburg: University Press.
Version
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Access right on openHSU
Open access