2018 - an IPA Odyssey: A single case study of how an Intelligent Personal Assistant should be constructed to align with the value proposition of Lynk & Co
Abstract
No one can forecast how the world will look like in the future, but one can tell that
it will be a completely different one from today. Companies are investing substantial amounts
of money in new technology, with one of the latest innovation being robots and how humans
want to interact with these. However, innovation does also repaint the competitive landscape,
and it has become significantly more important for manufacturing firms to put the customer
in the center rather than the product to stay competitive. While much research has been made
within the customer-centric approach and human-robot interaction which are the two
cornerstones of this thesis, there is a lack of literature where these two fields intersect. Thus,
the main purpose of this research is to investigate how Lynk & Co, our single-case study
manufacturing firm, should construct their Intelligent Personal Assistant in alignment with their
value proposition. This is performed through a qualitative study consisting of case-study
interviews with Lynk & Co managers and external HRI-experts. By first examining the two
cornerstones separately and subsequently combining these findings it was possible to shed
light on the thesis main research question. Findings showed that Lynk & Co adopt a customercentric
approach. Furthermore, twelve salient factors, strengthened by both theory and
empirical data, could be allocated in the Kano Model to assist Lynk & Co with the alignment
between their value proposition and the construction of their Intelligent Personal Assistant.
Degree
Master 2-years
Other description
MSc in Innovation and Industrial Management
Collections
View/ Open
Date
2018-08-02Author
Smith, Philip
Tollesson, Vincent
Keywords
HRI
Human-Robot Interaction
IPA
Intelligent Personal Assistant
Customer-centric
Service-dominant logic
User acceptance
Value proposition
Value proposition canvas
Series/Report no.
Master Degree Project
2018:72
Language
eng