Dr Takao Maruyama joined the School of Management in 2019 and is currently Assistant Professor in Business Analytics. He is also Programme Leader for MSc in Logistics, Data Analytics and Supply Chain Management (https://www.bradford.ac.uk/courses/pg/logistics-data-analytics-supply-chain-management/).
Prior to joining the School of Management, Takao had gained more than 10 years of industry experience in data analytics in the higher education sector, analysing various types of quantitative data and communicating effectively key findings with senior management teams.
Takao has worked on research areas including information systems, logistics and supply chain management, using data analytics. Lately, he has been working on research projects on social inclusion of minorities specifically older workers and their well-being/ job satisfaction. Takao has published papers in journals such as the Journal of Business Research, Information Technology and People, and New Technology Work and Employment.
The KTP project is proposed to be conducted between Incommunities, a UK social housing provider located in West Yorkshire and the School of Management, University of Bradford. This KTP project endeavours to embed within Incommunities an ethical data-driven business culture adopting an Artificial Intelligence (AI) based innovation strategy, in order to provide more effective support for their tenants who often suffer from problems such as unemployment and lack of income. The innovation within this KTP project is found in the application of AI and machine learning (machine learning being a subset of AI) to management decision making and service provision for its customers. For example, using AI/machine learning, it would become possible for Incommunities to predict potential requirements to repair appliances such as boilers. This would enable Incommunities to become more proactive rather than reactive, enabling them to schedule visits more effectively. Machine learning models would also enable the company to foresee possible non-payment by tenants. This would allow Incommunities to offer any relevant support necessary for those tenants before non-payment takes place. Therefore, the KTP project would make various business decision making processes at Incommunities automated, supported by AI and machine learning models. Simultaneously, the KTP project will ensure that AI and machine learning models are made ethical thereby making them transparent and explainable which can be intervened in order to comply with GDPR (General Data Protection Regulation). We will embed this ethical AI-driven organisational culture through action learning where key stakeholders within and without Incommunities will together explore and identify current issues the organisation faces, benefits and challenges potentially brought by AI-driven business strategy, and short-/long-term business goals supported by AI. In-house staff members within the Business Intelligence Unit will also learn from the Associate how to construct explainable AI and machine learning models through action learning. This way, the KTP project will steadily transform not only existing business intelligence system and business process within Incommunities but also stakeholders' understanding and attitudes toward the automated system.
I currently teach the following modules:
Srinidhi Karthikeyan;Takao Maruyama;Sankar Sivarajah (2024) Proceedings of the 26th International Conference on Enterprise Information Systems (ICEIS 2024). 1, 807-811.
Takao Maruyama;Charles Vincent (2025) Inside OR. Operational Research Society.
Takao Maruyama;Vincent Charles (2025) Significance. 22, 8-13.
Weerakkody V.;Sivarajah U.;Mahroof K.;Maruyama T.;Lu S. (2021) Journal of Business Research. 131
Tassabehji R.;Hackney R.;Maruyama T. (2019) Information Technology and People. 32
Maruyama T.;Tietze S. (2012) Personnel Review. 41, 450-469.
Maruyama, Takao; Hopkinson, Peter G.; James, P. (2009) NEW TECHNOLOGY WORK AND EMPLOYMENT. 24