A Proposed Evaluation Framework of Artificial Intelligence’s Business Effects on Sustainability from a Micro-enterprise Organizational Structure Type Perspective Using Fuzzy Intuitionistic Extensions


DEMİRCAN M. L., Ertan İ. C.

International Conference on Intelligent and Fuzzy Systems, INFUS 2024, Çanakkale, Turkey, 16 - 18 July 2024, vol.1088 LNNS, pp.575-583 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 1088 LNNS
  • Doi Number: 10.1007/978-3-031-70018-7_64
  • City: Çanakkale
  • Country: Turkey
  • Page Numbers: pp.575-583
  • Keywords: Artificial Intelligence, Decision Making, Fuzzy Intuitionistic Extensions, Micro-Enterprises, Sustainability
  • Galatasaray University Affiliated: Yes

Abstract

The increasing incorporation of Artificial Intelligence (AI) into corporate structures demands a thorough investigation of the implications for sustainability, especially in the complex environment of micro-enterprises. This study aims to provide a comprehensive assessment framework designed for examining the complex interactions between AI implementation and sustainability results, with a particular emphasis on the organizational structures characteristic of micro-enterprises. In order to acknowledge and account for the inherent uncertainties and imprecisions that characterize sustainability indicators in this dynamic setting, the proposed approach leans on fuzzy intuitionistic extensions. With a primary focus on sustainability issues, this study attempts to close current gaps in the academic discussion by offering a methodologically valid approach to evaluate the complex business implications of AI integration in the particular microenterprise environment. By utilizing fuzzy intuitionistic logic, the framework takes into account the natural desires and errors that come with sustainability metrics. This allows for a more realistic and nuanced representation of the complex relationships that exist between AI technologies and the organizational structures that are essential to micro-enterprises. Important components of the suggested assessment system include defining relevant sustainability aspects, creating fuzzy intuitionistic indicators relevant to micro-enterprises, and including a strict assessment process. By systematically utilizing this paradigm, our research aims to provide insightful information about the possible benefits and difficulties associated with implementing AI in micro-enterprises, so contributing to a more nuanced understanding of the technology’s implications for sustainable business practices. The expected results of this study will provide fundamental information for later academic investigations and guide policy decisions intended to promote ethical and sustainable AI adoption in the microenterprise space.