Artificial Neural Network approach for business decision making applied to a corporate relocation problem

Malik Haddad, David Sanders

Research output: Contribution to journalArticlepeer-review

205 Downloads (Pure)

Abstract

This paper presents a new Artificial Neural Network approach to making a business decision. A corporate relocation problem is considered as an example for a business decision and the new approach is applied to select a city for corporate relocation and to rank a set of potential alternatives. Selecting the location of corporate real estate can be key to optimizing an organization’s success. This is the first time Artificial Neural Networks have been used for this sort of business application. The Neural Network behaved satisfactorily and provided 91.76% accuracy when tested against randomly generated test sets. Five potential cities were considered: New York City, Washington D.C. Atlanta, Los Angeles and Portland. Decision makers identified six criteria: Financial Considerations Employee Availability, Support Services, Cultural Opportunities, Leisure Activities, and Climate. A suitable city is recommended that provides an appropriate solution and the outcome of the new approach is also used to rank potential cities based on their suitability.
Original languageEnglish
Pages (from-to)180-195
JournalArchives of Business Research
Volume8
Issue number6
DOIs
Publication statusPublished - 25 Jun 2020

Keywords

  • Artificial Neural Networks
  • Corporate Relocation
  • Multiple Criteria
  • Decision Making

Fingerprint

Dive into the research topics of 'Artificial Neural Network approach for business decision making applied to a corporate relocation problem'. Together they form a unique fingerprint.

Cite this