Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2019-2020 (archived)

Module BUSI4R015: Retail Science

Department: Management and Marketing

BUSI4R015: Retail Science

Type Tied Level 4 Credits 15 Availability Available in 2019/20 Module Cap None.
Tied to G5K709

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To provide students with a systematic way of understanding the role of data in management decision-making across the retail and distributive industries

Content

  • Fundamentals of retail management
  • Retail strategies – single-channel, multi-channel, omni-channel
  • Location management and intelligent network planning
  • Concepts in retail data analysis
  • Data requirements for market segmentation – geodemographic, psychographic, behavioural
  • Key metrics – Customer Lifetime Value, Marketing ROI, Scanner Data, EPOS, etc.
  • Brand management metrics and brand commerce models
  • Financial analytics in retail and distribution management

Learning Outcomes

Subject-specific Knowledge:
  • On completion of the module students should:
  • have a critical appreciation of the use of data in the retail and distributive trades;
  • be able to identify, collect, analyse and apply appropriate retail data forms and techniques;
  • have an advanced understanding of when system dynamics and data analytics might add value to the retail decision-making process.
Subject-specific Skills:
  • On completion of the module students should:
  • be able to scope data requirements from the description of a retail situation;
  • be able to build models to inform strategic decisions;
  • be able to understand customer behavioural data and conduct analysis on it;
  • be able to apply retail science to the analysis of real-world business situations.
Key Skills:
  • Effective written communication
  • Planning, organising and time management
  • Problem solving and data analysis
  • Making effective use of communication and information technology

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

  • The learning outcomes will be met through a combination of lectures, workshops and groupwork (including group discussion of case examples, data analysis exercises and a retail entrepreneurship simulation), together with individual exercises and guided reading.
  • During the course of the module, students complete a retail entrepreneurship simulation, scoping the data requirements for each stage in the process of setting up and managing a small business.
  • The summative assessment of the module, by individual written assignment, is designed to test students’ understanding and critical appreciation of the key concepts associated with retail science techniques, and their ability to apply them to complex problem solving.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 9 2 hours 18
Workshops 4 1 hour 4
Preparation and reading 128
Total 150

Summative Assessment

Component: Assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Individual written assignment requiring the application of retail analytics 3000 words (maximum) 100%

Formative Assessment:

Team project, based on a retail entrepreneurship simulation.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University