Revealing Sub-Optimality Conditions of Strategic Decisions

TL;DR

This paper investigates the dynamics of fitness landscapes in strategic decision-making, revealing how certain conditions lead decision makers to settle for sub-optimal solutions, supported by simulation results.

Contribution

It identifies specific dynamics causing premature termination of decision processes and compares traditional and research-based approaches in terms of optimality.

Findings

Correlation between Fitness Value and Probability of Optimality is significant.

Traditional decision-making approaches often result in sub-optimal outcomes.

Research-based approaches tend to reach higher fitness and optimality.

Abstract

Conceptual view of fitness and fitness measurement of strategic decisions on information systems, technological systems and innovation are becoming more important in recent years. This paper determines some dynamics of fitness landscape which are lead to termination of decision makers' research before reaching the global maximum in strategic decisions. These dynamics are specified according to management decision making models and supported with simulation results. This article determines simulation results by means of "Fitness Value" and "Probability of Optimality". Correlation between these two concepts may be remarkable according to revealing optimal values in innovative and research-based decision making approaches beside sub-optimal results of traditional decision making approaches.