Module BUSI4AX15: Practice of AI in Business Research

Department: Management and Marketing

BUSI4AX15: Practice of AI in Business Research

Prerequisites

• None

Corequisites

• None

Excluded Combination of Modules

• None

Aims

• This module explores how AI is transforming research practices in marketing and management, focusing on applications, ethical considerations, and future directions. It aims to:
• Make students aware of cutting-edge AI technologies in tackling real-world challenges across different research fields and their relevance in business research,
• Equip students with relevant knowledge and experience to understand how AI enhances data collection, analysis and insight generation,
• Develop students’ understanding of real-world case studies and academic research using AI,
• Make students engage with a seminal paper in practice of AI and critically present its content in an accessible way to other PhD students.

Content

• The module will explore the recent developments and real-world applications of AI and data analytics in the fields of management and marketing.
• We examine how AI is being used to address challenges and drive innovation across a range of research fields such as supply chain management, operations management, human resource management, organisational behaviour and leadership, marketing science, and consumer behaviour.
• Empirical research and real-world case studies will be used to develop a deep understanding of how AI is shaping the future of key areas in business research.

Learning Outcomes

• By the end of this module, students will gain advanced, domain‑specific knowledge in the following areas:
• Foundations in AI for business research:
• - understanding core AI concepts and emerging technologies shaping empirical business research.
• Applications of AI across management and marketing domains:
• - exploring how AI tools address research challenges across marketing, operations, HR, leadership, organisational studies and so on
• - examining real‑world applications of AI and how they support decision‑making, innovation, and organisational performance.
• Critical engagement with emerging research: understanding methodological choices, data collection and analysis, and being aware of various ethical issues (such as privacy, transparency, and so on) and their limitations.

• By the end of the module students should be able to:
• Demonstrate a good overview of recent developments in AI and their applications to various research fields,
• Critically evaluate innovative and advanced research in management and marketing, and understand ethical and strategic implications of AI in research,
• Investigate AI related research topics independently, review the relevant literature competently and understand the underlying concepts.

• Students are expected to:
• Develop communication skills on high level of conceptual understanding of specific research and appropriate use of referencing,
• Read, interpret and critically evaluate seminal papers and frontier research applying AI in business,
• Undertake advanced academic reading and writing at doctoral level, and
• Give a clear and concise oral presentation to academic peers demonstrating their understanding of the chosen topic.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• The module will be delivered in a blended format, including workshops with lecture-type delivery elements, class discussion and academic presentations; and guided work in small online tutorial groups that helps students develop a deeper understanding of doctoral-level research.
• Overview of AI in specific research areas will be presented by academic staff at each session. Students will be encouraged to explore interdisciplinary research topics in management and marketing, to critically review the relevant articles and present to their peers. Comprehensive reading and research articles will be provided.
• The summative assessment is designed to deepen students’ understanding of AI driven approaches and how to apply them in empirical research projects within the chosen field of Management and Marketing.
• The group-based formative assessment encourages peer learning, fosters a strong doctoral community, and helps them to develop essential teamwork skills for collaborative research.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Each group will prepare one page (A4) presentation proposal to be submitted one week before the presentation takes place. For this, each group may have at most two preparatory meetings (face-to-face or online) with the module leader to refine the presentation, clarify outstanding issues they may have on the assigned research paper and so on.

■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.