MAR529 Front Lines on Adoption of Digital and AI-Based Services

• Topics

  The course aims to provide exposure to current topics in digital businesses and the tools required to pursue research in the domains of digitalization at large, and consumer-firm interactions. At the organizational level, the impact of digitalization is largely fostered by the adoption of Intelligent Automation (IA) and Artificial Intelligence (AI) by customers and employees. Hence, the current course builds on theoretical, conceptual, and methodological advances from the following research streams: digital strategy, innovation and ecosystems, digital marketing, and consumer behavior.                                                                                                                           

  The course format integrates seminar-based readings, lectures, hands-on exercises, and presentations. Students are expected to learn not only the diverse applications of digitalization in various consumer spaces including advertising but also gain exposure to the various types of data sources available to propose new research ideas.

  During the course, the students will gain an overview of the front lines of IA & AI adoption and the impact of digitalization on businesses and public policy. Students will be exposed to an in-depth understanding of digitalization when creating and capturing value. The sessions will cover lectures from diverse research areas such as behavioral economics, marketing finance, consumer online search, adoption of new products and services, etc.

  One of the biggest areas where IA & AI has affected businesses is in the consumer-firm service delivery and communication space. The adoption of image recognition, language technology, and predictive modeling are three areas where IA & AI have made a difference. Consequently, the next part of the course focuses on the macro as well as the micro aspects of adopting IA & AI-based services in businesses. Students will read and understand ethics, personalization, privacy, and other related topics.

  The course also provides the required impetus for the students to become aware of various data sources available for analysis. The students will get an overview of methods and tools for analyzing text and audio data.

  The course concludes with students presenting their research proposal ideas which will be the first part of the term paper for the course.

• Learning outcome

  After completing the course, the students are able to:

  Knowledge

  • argue for theories and constructs about the implications of AI for Businesses
  • apply these theories and constructs to Marketing & Consumer Behavior
  • argue for key theories and constructs specific to Marketing & Consumer Behavior
  • account for key patterns in empirical findings regarding this relationship
  • understand the key methodologies employed in the context of AI & Marketing

  Skills

  • understand and discuss the degree to which different theories and constructs are complements or substitutes
  • relate new empirical findings to underlying theoretical concepts
  • formulate relevant and interesting research questions at the intersection of Marketing & AI

  General competence

  • absorb, communicate, discuss, and evaluate research at the intersection of AI & Marketing/Consumer Behavior at the research frontier
  • contribute to AI discussions in marketing strategies of the firm

• Teaching

  TEACHING

  Teaching will be physical. Some sessions will be through Teams/Zoom.

  Teachers 

  • Introduction/overview of IA & AI, Professor Tor W. Andreassen , Director  Jim Spohrer
  • AI, IA, and analytics in business. What’s it all about? Associate professor  Ivan Belik, Professor  Tor W. Andreassen
  • Front lines in adopting IA & AI in service + Initial brainstorming of term paper topics, Tor W Andreassen, Professor  Helge Thorbjørnsen , Assistant professor Darius-Aurel Frank
  • Trends in digital communication, personalization, regulation, and ethics + Term Paper Topics Feedback, Professor Tor W. Andreassen , Assistant professor  Aruna D. Tatavarthy, PhD candidate  Jareef Martuza 
  • Overview of chatbots in research and business, Professor Tor W. Andreassen, PhD candidate  Denis Utochkin
  • Presentations of and feed-back on research proposals, Teaching faculty

  BOLD = Featured professor. A more detailed schedule will be presented during the introduction. Students are expected to prepare the course literature prior to the class.

• Restricted access

  Maximum 20 students (pedagogical reasons).

   

  PhD candidates from NHH and other Norwegian institutions, as well as PhD candidates from institutions, which are part of Engage.eu network, and NHH’s Innovation Index Research Partnership, can attend the course. DIG partners can also participate.

  Priority: PhD candidates from NHH.

  Second priority: PhD candidates from Engage-network, and other Norwegian institutions.

  Third priority: PhD candidates associated with institutions, which are part of NHH’s Innovation Index Research Partnership.

  Fourth priority: DIG partners.

  External Research Scholars: We kindly request you send an application to attend the course https://www.nhh.no/en/study-programmes/phd-programme-at-nhh/phd-courses/become-a-visiting-student-at-a-phd-course-at-nhh

• Recommended prerequisites

  Master level marketing knowledge.

• Required prerequisites

  This course is ideal for PhD candidates who are one to two years into the program.

• Compulsory Activity

  • Students have to present at least one article in class.
  • Students are expected to participate actively in class discussions.

• Assessment

  An individual term paper on a predefined topic at the heart of the course is written in English. Electronic hand-in of term paper in Wiseflow.

• Grading Scale

  A-F

• Computer tools

  Bring your own computer.

• Literature

  • Compendium of articles and book chapters.
  • The course schedule with a complete list of readings, will be available in due time prior to the seminar.