BUS470 Retail Analytics

• Topics

  Retail firms occupy a large share of the workforce, provide career opportunities, and the functioning of retail markets are central to the economy. Retailing has undergone significant changes in terms of digitalization, technology and the vertical and horizontal structure during the last decades. From smaller independent units to larger chains, from a fragmented independent wholesale sector to concentrated chain-owned distribution, from national - to partly international ownership, to mention some of the major trends. The newest and most important change is the challenge met by traditional brick-and mortar stores from the new online stores.

  The course aims to give the students a better understanding of the functioning and the mechanisms that are important in the retail sector. We will focus on factors important to decision making on pricing, and discuss how the various business models that coexist in a changing retail environment affect both firms and the sector at large. We will combine theory and empirics, using real data from various retail sectors and provide the students with analytical tools that can be used in the retail sector. The course will also introduce the students to key persons working in the sector through a number of guest lectures.

  The students will learn how to analyze data and problems using real data from the retail sector.

  A student that has taken this course should be able to start working in strategy- and analysis departments in major retail chains, having a skillset that includes a strategic understanding of retail markets and data analyst skills that can be used to handle datasets.

  Topics that will be covered include:

  • The retail sector at large
  • The history of retailing in Norway
  • Technological development, productivity and innovation
  • From independent wholesalers to centralized distribution
  • The vertical structure of retailing
  • From Brick and mortar to Amazon
  • Horizontal organization and competition

  Pricing dynamics and demand

  • Pricing dynamics and algorithmic pricing
  • How does new (sugar) tariffs affect pricing?
  • Fast moving consumer goods - price search and pricing obfuscation
  • Pricing and the business cycle
  • Demand when both quality and price matters
  • Demand for online goods
  • Self-Checkout: Does it change consumer behavior?

  Competition and local markets

  • Local market delineation in retail industries: Diversion ratios and price pressure tests
  • Cross border trade in grocery markets
  • Car retailing and competition
  • Competition in local pharmacy markets
  • Local market power in gasoline retailing
  • Asymmetric price responses in gasoline markets: Rockets and Feathers

  Some of the retail sectors discussed more in detail during the course:

  • Grocery
  • ‘Dollarstores’
  • Pharmacies
  • Gasoline
  • Cars
  • Online retail

• Learning outcome

  Knowledge:

  • In-depth knowledge on the retail sector and its functioning.
  • Be able to use economic theory to better understand retail markets.
  • Be able to use retail sector data to estimate pricing, demand and competition effects.

  Skills:

  • Use economic modelling to understand retail market dynamic.
  • Analyze and evaluate retail data using statistical tools.
  • Formulate and estimate simple dynamic pricing models.
  • Formulate and estimate simple demand models.
  • Formulate and estimate differentiated demand models.
  • Formulate and estimate competition models.

  General competence:

  • Understand how retail markets work and interpret these using economic theory and data.
  • Provide ethical justification for how to design and understand research on retail markets.

• Teaching

  The major part of the teaching will take place in classes (15), but we also have three lab sessions during the course. We will have a number of guest lectures from key-industry people (2-3).

  The lectures will be given physically in the auditorium as often as possible. However, since two of the lecturers are not local, some lectures will be given using zoom.

  The labs will be physical, and none of the auditorium teaching will be streamed.

• Recommended prerequisites

  Retail Analytics will use Industrial Organization models and apply analytical tools like STATA. Thus former knowledge on these topics will be an advantage. The latter is for instance covered in courses like ECN 433 Competition Strategy (earlier: BUS441) and methodology courses from BUS, BAN or ECN in regression techniques.

• Compulsory Activity

  Two mandatory assignments solved in groups (maximum three group members).

• Assessment

  One four-day home exam solved in groups (maximum three group members), start Day 1 at 09:00, deadline Day 4 at 14:00.

  The exam must be written in English. 

• Grading Scale

  A-F

• Computer tools

  We will use STATA in class and in the labs, but it is possible to solve the assignments also using R

• Literature

  Textbook and articles