Dynamic linkages between mental models, resource constraints and differential performance

The purpose of this paper is to focus around the literatures of the resource-based firm and cognitive mental models, explores the dynamic linkages between cognitive models, resources and firm performance in the context of the insurance industry. In a real-life example drawn from the insurance indust...

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Bibliographic Details
Main Authors: Mandal, Abhijit, Thomas, Howard, Antunes, Don
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/3814
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Institution: Singapore Management University
Language: English
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Summary:The purpose of this paper is to focus around the literatures of the resource-based firm and cognitive mental models, explores the dynamic linkages between cognitive models, resources and firm performance in the context of the insurance industry. In a real-life example drawn from the insurance industry, a process-based simulation model is developed to explore the linkages between managerial mental models, resources and performance. It represents resources as endogenous flows and mental models and resource constraints as exogenous parameters. This allows, for example, the impact of heterogeneity in mental models, on such factors as the time path of resource allocations, resources and capabilities, and ultimately performance, to be studied in two firms (business units) in the insurance industry. In general, heterogeneity in mental models leads to differences in performance in the long run. This finding is reinforced by the presence of resource constraints. Facing strategic change, however, it is often difficult for senior managers to overcome the influence of well-established managerial mental models or recipes which create cognitive inertia and, in turn, hinder performance improvements. There are few empirical studies which explore the impact of changes in mental models and resource constraints on firm-performance and resource allocation decisions.