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.

Highlights

  • This paper presents a new Artificial Neural Network (ANN) approach to assist with business decisions

  • Los Angeles was identified as the best city to relocate by Analytical Hierarchy Process (AHP) and PROMETHEE II in [1]

  • The new approach provided the same ranking of cities to relocate based on their suitability

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Summary

INTRODUCTION

This paper presents a new Artificial Neural Network (ANN) approach to assist with business decisions. This is the first time ANN have been used in this way and for this sort of application. After data were processed through the layers, the network could recognize the appropriate identifiers for classifying the data to appropriate classes [19] Due to their classification and predictive capabilities, ANNs could produce suitable and reliable outcomes for corporate location problems.

Atlanta
DISCUSSION AND RESULTS
CONCLUSION AND FUTURE WORK
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