Gigification, job engagement and satisfaction: the moderating role of AI enabled system automation in operations management

Abstract

Innovative and highly efficient Artificial Intelligence System Automation (AI-SA) is reshaping jobs and the nature of work throughout supply chain and operations management. It can have one of three effects on existing jobs: no effect, eliminate whole jobs, or eliminate those parts of a job that are automated. This paper focuses on the jobs that remain after the effects of AI-SA, albeit with alterations. We use the term Gigification to describe these jobs, as we posit that the jobs that remain share characteristics of gig work. Our study examines the relationship between Gigification, job engagement and job satisfaction. We develop a theoretical framework to examine the impact of system automation on job satisfaction and job engagement, which we test via 232 survey responses. Our findings show that, while Gigification increases job satisfaction and engagement, AI-SA weakens the positive impact of Gigification on these important worker outcomes. We posit that, over time, the effects of AI-SA on workers is that full-time, permanent jobs will give way to gigified jobs. For future research, we suggest further theory development and testing of the Gigification of operations and supply chain work.

Keywords:

• Artificial intelligence
• job satisfaction
• job engagement
• gigification
• operations management
• system automation
• supply chain management

Additional information

Notes on contributors

Ashley Braganza

Professor Ashley Braganza is Deputy Dean for the College of Business, Arts and Social Sciences and holds the Chair in Organizational Transformation. He is the founder of the Centre for Artificial Intelligence. His research interests encompass the effects of AI, big data, change management, strategy implementation, process and knowledge management and transformation enabled information systems. He has published over 100 papers in prestigious academic and practitioner journals and three books. He has carried out over 50 consultancy assignments with large public and private organizations.

Weifeng Chen

Weifeng Chen specializes in technological adoption and innovation management. He is a founding member of the Centre for Artificial Intelligence, at Brunel University London. His current research focuses on the impact of Artificial Intelligence on business models and value chain optimization. More broadly his research explores the contemporary issues in international strategic product, service, and organizational innovation management.

Ana Canhoto

Ana Isabel Canhoto is a Reader in Marketing, and a founding member of the Centre for Artificial Intelligence, at Brunel University London. Her research focuses on the use of digital technology in interactions between firms and their customers, including the role of algorithmic decision making in customer interactions, or the use of digital technology for customer insight. She has taught across various programmes, including MBA and executive education, and has led on the pedagogical use of new technologies including being an adviser on the design of the Google Online Marketing Challenge.

Serap Sap

Serap Sap is a Lecturer in Marketing, Abdullah Gul University, Kayseri. She has received her PhD degree in Marketing from Brunel Business School at Brunel University London, UK. She holds an MBA degree with a Marketing concentration from LeBow College of Business, Drexel University, USA. Her research interests include Corporate Brand, SME Marketing, Innovation and Artificial Intelligence.