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Line and Staff Functions in Organizations Revisited: A Bionic System Analogy Using ISM

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  • Alpana Agarwal
  • Prem Vrat

Abstract

The purpose of this article is to identify variables and their interrelationships causing line and staff conflict in organizations. Specifically it is comparing and analyzing the causes of line and staff conflict from human body perspective, assuming it to be an optimally managed organization. A generally applicable framework that establishes relationship between these variables is developed using interpretative structural modelling (ISM). The developed framework is then compared with the organization of line and staff functions in the human body, presuming that with this the real cause of the problem could be understood. In this effort, it has been found that an optimal degree of flexibility, top management involvement, equity, clearly defined roles and appropriate design and reporting relationships are the major strategies followed by human body that can help managers to eliminate conflict. It is expected that based on this comparison some ways of resolving conflict within organizations can be suggested. Besides, we can also expect that mimicking a variety of elements in human body organization can inspire business organizations to learn improvements in their design and function too.

Suggested Citation

  • Alpana Agarwal & Prem Vrat, 2015. "Line and Staff Functions in Organizations Revisited: A Bionic System Analogy Using ISM," Vision, , vol. 19(2), pages 89-103, June.
    • Handle: RePEc:sae:vision:v:19:y:2015:i:2:p:89-103
    DOI: 10.1177/0972262915575651
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    References listed on IDEAS

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    1. M.N. Qureshi & Dinesh Kumar & Pradeep Kumar, 2007. "Modeling the logistics outsourcing relationship variables to enhance shippers' productivity and competitiveness in logistical supply chain," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 56(8), pages 689-714, November.
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    Cited by:

    1. Sushil, 2018. "How to check correctness of total interpretive structural models?," Annals of Operations Research, Springer, vol. 270(1), pages 473-487, November.

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