Managerial economics

About: Managerial economics is a research topic. Over the lifetime, 1524 publications have been published within this topic receiving 83965 citations.

Artificial Economics: What, Why and How

Abstract: In this paper we present our views on the distinguishing features of Artificial Economics and on its relation with Theoretical Economics – the field that in our opinion lies closest to Artificial Economics. In this context, we discuss various reasons why conducting research on Artificial Economics may be worthwhile, and provide general guidelines on how to go about it. Our view is that Artificial Economics and Theoretical Economics share the same goals, do not differ conceptually as much as it is sometimes perceived, and their approaches are certainly complementary.

DEMAND FORECASTING: EVIDENCE-BASED METHODS Forthcoming in the Oxford Handbook in Managerial Economics Christopher R. Thomas and William F. Shughart II (Eds.) Subject to further revisions

Abstract: We reviewed the evidence-based literature related to the relative accuracy of alternative methods for forecasting demand. The findings yield conclusions that differ substantially from current practice. For problems where there are insufficient data, where one must rely on judgment. The key with judgment is to impose structure with methods such as surveys of intentions or expectations, judgmental bootstrapping, structured analogies, and simulated interaction. Avoid methods that lack evidence on efficacy such as intuition, unstructured meetings, and focus groups. Given ample data, use quantitative methods including extrapolation, quantitative analogies, rule-based forecasting, and causal methods. Among causal methods, econometric methods are useful given good theory, and few key variables. Index models are useful for selection problems when there are many variables and much knowledge about the situation. Use structured procedures to incorporate managers’ domain knowledge into forecasts from quantitative methods where the knowledge would otherwise be overlooked, but avoid unstructured revisions. Methods for combining forecasts, including prediction markets and Delphi, improve accuracy. Do not use complex methods; they do not improve accuracy and the added complexity can cause forecasters to overlook errors and to apply methods improperly. We do not recommend complex econometric methods. Avoid quantitative methods that have not been properly validated and those that do not use domain knowledge; among these we include neural nets, stepwise regression, and data mining. Given that many organizations use the methods we reject and few use the methods we recommend, there are many opportunities to improve forecasting and decision-making.

Beyond Positivism and Normativism

Abstract: The author rejects the usual division of economics (Positive Economics versus Normative Economics). Since actions and perceptions are not contrary but complementary phases of the same process such an economics seems to be right which is able to serve both economic actions and perceptions. The author argues for the utilization of the Action Research and Evaluation Research methodologies in economics. In the light of these methodologies the constructive and valuative aspects of economics are desirable. Constructive economic researches discover, new earlier non-existent possibilities for the economic activities. Valuative economic researches explicitly valuate the ways economic activities actually run. Constructive and Valuative Economics seems to be appropriate for making of a better economic world than we live in now.

Management in Perspective: The Tactics of Jungle Warfare

Abstract: The article discusses the challenges of teaching the science and theory of management. The author creates an analogy of the management theory jungle and compares the teaching of management science ...