Loading…

Comparing multi-dimensional contingency fit to financial performance of organizations

In theory, it is widely accepted that an organization’s optimal structure is contingent upon various situational factors such as market conditions, nature of work and properties of technology. In practice, providing practical advice based on this understanding has been difficult. This paper demonstr...

Full description

Saved in:
Bibliographic Details
Published in:European journal of operational research 2009-05, Vol.194 (3), p.911-921
Main Authors: Nasrallah, Walid F., Qawasmeh, Suleiman J.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In theory, it is widely accepted that an organization’s optimal structure is contingent upon various situational factors such as market conditions, nature of work and properties of technology. In practice, providing practical advice based on this understanding has been difficult. This paper demonstrates that it is possible to find a correlation between financial performance, as measured by growth in Return on Assets, and degree of compliance with the recommendations of the contingency theory model known as Interaction Value Analysis (IVA). IVA is based on an abstract theoretical representation of organizational work as a series of value-adding interactions among rational value-maximizing agents. Six different dimensions of an organization’s situation are represented as parameters of the equation that sums up the value added by all interactions within the organization. This “Multi-dimensional” approach is contrasted with the “Multi-contingency” model, which aggregates the effects of multiple contingent-design rules without considering how the rules overlap or otherwise influence one another. The success of the six-parameter IVA model in partially predicting financial performance is an inducement to expand IVA to include more of the parameters included in the Multi-contingency model.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2008.01.011