Supply Chain and Business Technology Management

Description:

This research seminar is offered in three modules. The conceptual aspects of digital innovation, digitalization, and digital transformation are covered in Module I. Module II focuses on digital entrepreneurship and innovation. Individual and societal impacts of digital technologies and innovation are discussed in Module III. The main goals of this seminar are to: i) understand the research and managerial issues related to digital innovation, digital entrepreneurship, and individual and societal impacts of new technologies and innovations, ii) review the underlying theories in different disciplines such as management information systems, strategic management, entrepreneurship, and marketing, and iii) synthesize academic articles in order to identify major research and management themes within and across topics. The integrative coverage of topics provides students in various disciplines such as management information systems, management, marketing, and finance with the necessary knowledge to conduct conceptual and empirical research on interdisciplinary topics in digital innovation.

Component(s):

Seminar

Description:

The course provides an overview of how diffusion and adoption of emerging hard and soft technologies shape modern supply chain management. Adoption of these technologies results in a shift from the traditional linear and sequential supply chain operations towards interconnected, open system supply networks. How these advances impact the tenets of modern supply chain management are discussed in terms of operations planning, risk management, sourcing, and logistics, among others. Hybrid learning mediums involving lectures, research article presentations, cases, games and/or guest lecturers are used for course delivery.

Component(s):

Seminar

Description:

Special topics in supply chain management, business technology management and/or business analytics are covered. The specific course description is made available prior to the registration period.

Component(s):

Seminar

Description:

Students in this course explore big data, artificial intelligence concepts and algorithms with a major focus on business applications. Among others, the topics covered are search methods, knowledge representation and reasoning, decision making under uncertainty, and machine learning. Through hands-on projects in different functional areas of business, students are exposed to genetic algorithms, particle swarm optimization, artificial neural networks, ensemble learning, and deep learning including performance evaluation, error reduction and empirical validation. For a managerial problem identified, students conduct a review of relevant literature and implement an intelligent system using specialized software.

Component(s):

Seminar