Front Lines on Adoption of Digital and AI-Based Services

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

Autumn 2022

  • Topics

    The aim of the course is to provide the exposure of current topics in digital businesses and 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 on 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 in businesses and public policy. Students will be exposed to 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 modelling 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 about 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, and the students will get an overview of methods and tools for analyzing text-data and audio-data.

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

  • Learning outcome


    • Argue for theories and constructs about implications of AI to 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


    • 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

    • Evaluate research at the intersection of AI & Marketing/Consumer Behavior at the research frontier
    • Contribute to AI discussions in marketing strategies of firm

  • Teaching


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

    Week 43: Teaching from 09:00 to 17:00. (Teaching time for Sunday will be announced later)

    Teachers (tentative)

    • Sunday:  Introduction/overview of IA & AI, Tor W. Andreassen, Jim Spohrer
    • Monday:  Creating and capturing value in a digital era; digital strategies and consumer trends, Tor W. Andreassen, Roland Rust, Tina Saebi/ Magne Angelshaug,
    • Tuesday:  Front lines in adopting IA & AI in service, Tor W Andreassen, Helge Thorbjørnsen, Darius-Aurel Frank
    • Wednesday: T rends in digital communication, personalization, regulation, and ethics,  Tor W. Andreassen, Aruna D. Tatavarthy
    • Thursday:  Overview of AI-based methods for research, Tor W. Andreassen, Nhat Q Le, Mansur Khamitov
    • Friday:  Presentations of and feed-back on research proposals, Teachers present depent on topics for presentation

    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 NHH’s Innovation Index Research Partnership, can attend the course. DIG-partners can participate, if there are available capacity, but will not develop a term paper for evaluation.

    External Research Scholars: We kindly request you send an application to attend the course

    First priority: PhD candidates from NHH.

    Second priority: PhD candidates from other Norwegian institutions.

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

    Fourth priority: DIG partners.

  • Recommended prerequisites

    Master level marketing knowledge.

  • Compulsory Activity

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

  • Assessment

    Individual term paper written in English. 

  • Grading Scale

    Pass - Fail.

  • 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.


ECTS Credits
Teaching language

Autumn. Offered Autumn 2022.

Course responsible

Professor Tor Walin Andreassen, Department of Strategy and Management