Demand and supply of FM outsourcing services

A sustainable artificial intelligence facilities management outsourcing relationships system: Case studies

The purpose of this article was to validate the published artificial intelligence (AI) facilities management (FM) outsourcing relationships system by real business cases in the working environment. The research aims to inspire the modern FM professionals in different industries with some challenging and innovative concepts about FM outsourcing relationships between facilities owners and service providers. First, it will briefly introduce the theory of the FM outsourcing relationships system on how it can help the FM seniors and strategists to design their FM daily strategies wisely and make their business more effective and productive. Second, it will also introduce what the research is practically doing in the stage of case study for test and verification. It is concluded that FM outsourcing categorization may help to define the appropriate relationships. This further detailed outcome generated from the AI can be considered a solid reference to define and explain the existing outsourcing relationships between the stakeholders and the service providers to assign an outsourcing category to the FM relationship between the client and service provider based on the learnt rules.

A Sustainable Facility Management Outsourcing Relationships System: Artificial Neural Networks

The Contingency Outsourcing Relationship (CORE) model originated from the Four Outsourcing Relationship Types (FORT) model; the CORE model is used in the globalized Facility Management (FM) industry, while the FORT model is originally used in the global information technology industry. The purpose of this paper is to thoroughly analyse the simulated case studies of the four different categories (i.e., in-house, technical expertise, commitment and common goals) of the CORE model from the perspective of the various clients. This study builds on the previous work on the outsourcing relationships between a client and a globalized FM service provider. It further explores the application of this model with the aid of artificial neural networks (ANNs) towards a sustainable future. A quantitative methodology through a survey is used to analyse eight outsourcing strategies for the four outsourcing relationships. A set of revised rules of the CORE is introduced and discussed regarding the approaches to investigate the four simulated outsourcing relationship systems. The study further reveals that an interesting understanding of the four outsourcing categories can be systematically and efficiently implemented into the FM outsourcing relationships through the methodology of scientific Artificial Intelligence (AI). It is concluded that FM outsourcing categorization may help to define the appropriate relationships. This further detailed outcome generated from the ANN can be clearly considered a strong and solid reference to define and explain the existing outsourcing relationships between the stakeholders and the service providers with the aim to assign an outsourcing category to the FM relationship between the client and service provider based on the learnt rules.