TY - JOUR
T1 - A comprehensive analysis of the implications of artificial intelligence adoption on employee social well-being in South African facility management organizations
AU - Moghayedi, Alireza
AU - Michell, Kathy
AU - Awuzie, Bankole
AU - Adama, Unekwu Jonathan
N1 - Publisher Copyright:
© 2024, Emerald Publishing Limited.
PY - 2024/7/19
Y1 - 2024/7/19
N2 - Purpose: The purpose of this study is to explore the increased uptake of Artificial Intelligence (AI) technology by Facility Management (FM) organizations for enhanced operational efficiency and competitive advantage. While AI adoption in FM has been widely reported, limited attempts have been made to assess its impact on the social well-being of FM employees. To contribute towards addressing this gap, this study established the essential employee social well-being factors mostly impacted by the adoption of AI in South African FM organizations. Design/methodology/approach: A four-stage design comprising a comprehensive review of literature, expert interviews, questionnaire census and focus group discussion sessions was used to elicit data from a sample of participants drawn from 22 South African FM organizations. The data was analyzed using a combination of content analysis, relative importance index and interpretative structural modeling for various data sets toward achieving the study’s objectives. Findings: Sixteen employee social well-being factors, classified under job satisfaction, social relationship and knowledge development categories, respectively, were identified as being impacted by AI adoption in FM organizations. Furthermore, it was established that job security, job autonomy and professional status, which belong to the job satisfaction social well-being factor category, were deemed by FM employees as being mostly impacted by AI adoption. Practical implications: The enhanced understanding of the impact of AI adoption on FM employees’ social well-being factors will contribute to the development of a collaborative intelligence framework for managing AI adoption in FM organizations toward engendering optimal AI–FM employee relationships for improved productivity. Originality/value: Besides being one of the foremost studies to investigate the impact of AI adoption on FM employees’ social well-being, this study introduces a hierarchical framework of understanding employee social well-being factors based on multi-stakeholder perspectives.
AB - Purpose: The purpose of this study is to explore the increased uptake of Artificial Intelligence (AI) technology by Facility Management (FM) organizations for enhanced operational efficiency and competitive advantage. While AI adoption in FM has been widely reported, limited attempts have been made to assess its impact on the social well-being of FM employees. To contribute towards addressing this gap, this study established the essential employee social well-being factors mostly impacted by the adoption of AI in South African FM organizations. Design/methodology/approach: A four-stage design comprising a comprehensive review of literature, expert interviews, questionnaire census and focus group discussion sessions was used to elicit data from a sample of participants drawn from 22 South African FM organizations. The data was analyzed using a combination of content analysis, relative importance index and interpretative structural modeling for various data sets toward achieving the study’s objectives. Findings: Sixteen employee social well-being factors, classified under job satisfaction, social relationship and knowledge development categories, respectively, were identified as being impacted by AI adoption in FM organizations. Furthermore, it was established that job security, job autonomy and professional status, which belong to the job satisfaction social well-being factor category, were deemed by FM employees as being mostly impacted by AI adoption. Practical implications: The enhanced understanding of the impact of AI adoption on FM employees’ social well-being factors will contribute to the development of a collaborative intelligence framework for managing AI adoption in FM organizations toward engendering optimal AI–FM employee relationships for improved productivity. Originality/value: Besides being one of the foremost studies to investigate the impact of AI adoption on FM employees’ social well-being, this study introduces a hierarchical framework of understanding employee social well-being factors based on multi-stakeholder perspectives.
KW - Artificial intelligence
KW - Employee
KW - South Africa
UR - http://www.scopus.com/inward/record.url?scp=85196272565&partnerID=8YFLogxK
U2 - 10.1108/JCRE-09-2023-0041
DO - 10.1108/JCRE-09-2023-0041
M3 - Article
AN - SCOPUS:85196272565
SN - 1463-001X
VL - 26
SP - 237
EP - 261
JO - Journal of Corporate Real Estate
JF - Journal of Corporate Real Estate
IS - 3
ER -