Models of Strategic Management Scanning Based on Trend Heuristics as the Least Information Intensive Quantifiers

Abstract

SS (Strategic Scanning) is unique, partially subjective, inconsistent, interdisciplinary, vague and multidimensional process. Its description and optimisation suffers from IS (Information Shortage) and heterogeneity. IS eliminates straightforward application of traditional statistical methods. Heterogeneity problems are caused by heterogeneous nature of scanned information structures. Artificial Intelligence has developed some tools to solve such problems. Qualitative reasoning is one of them. It is based on the least information intensive quantifiers i.e. trends. There are four different trends i.e. qualitative values and their derivatives: plus/increasing; zero/constant; negative/decreasing; any value / any trend. The paper studies SS models based on ELEs (Equationless Heuristics). An example of ELE is – If novelity is increasing then confidence is decreasing. A solution of a qualitative model is represented by a set S of scenarios and a set T of time transitions among these scenarios. The key information input into an ELE model is subjective knowledge of experts. A consensus among SS experts is often not reached because of inconsistencies of experts’ knowledge. The SS case study is 12 dimensional (e.g. Freshness, Relevance) and based on 12 ELEs. There are 29 scenarios.