The legitimacy theory and the legitimacy gap

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

In this chapter, we discuss the legitimacy theory and the legitimacy gap. Organizations seek to be perceived by stakeholders as legitimate. Because legitimacy is a moving target, organizations have to be pragmatic. The legitimacy gap will be formed due to the concept of time, which informs the movement of expectations. As time progresses, the environment in which organizations operate will shift, which would create a shift in expectations. This change brings a shift to legitimacy, and this shift creates a “legitimacy gap”. On the basis of this, Lindblom (1994) defines the legitimacy gap as “the difference between the expectations of the relevant stakeholders relating to how an organization should act, and how the organization does act”. Essentially, two main sources of the legitimacy gap were outlined, namely, the changes in societal expectation and information asymmetry. We outlined the role of AI in moderating the legitimacy gap, specifically if the concept of information asymmetry is deemed the main driver of the gap. In the context of harvested and stored large data sets, we suggest that intelligent agents linked (connected) to the relevant data repositories would be updated on an ongoing basis as the new data is being captured or it becomes available through unstructured sources. This data would previously have been difficult to collate. We point out that social media and other sources would make it possible to harvest this data. We think that once harvested, AI-powered models will analyse it, which will assist organizations in predicting expectations. In cases where society is too weak, perhaps authorities could deploy the same technology on behalf of societies that are unable to, in order to reduce the information gap between the organization and the society.

Original languageEnglish
Title of host publicationAdvanced Information and Knowledge Processing
PublisherSpringer
Pages103-113
Number of pages11
DOIs
Publication statusPublished - 2020

Publication series

NameAdvanced Information and Knowledge Processing
ISSN (Print)1610-3947
ISSN (Electronic)2197-8441

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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