Making sense of digital innovation

The rapid development of digital technologies has been reshaping the way of designing products, services, and business models by stimulating remarkable innovations to industries. Specifically, the paradigm of production in digital products has shifted from merely increasing hardware parameters to pr...

Full description

Saved in:
Bibliographic Details
Main Author: Zhang, Nila
Other Authors: Sia Siew Kien
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/136949
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-136949
record_format dspace
spelling sg-ntu-dr.10356-1369492024-01-12T10:20:36Z Making sense of digital innovation Zhang, Nila Sia Siew Kien Nanyang Business School asksia@ntu.edu.sg Business::Information technology::Management of information systems The rapid development of digital technologies has been reshaping the way of designing products, services, and business models by stimulating remarkable innovations to industries. Specifically, the paradigm of production in digital products has shifted from merely increasing hardware parameters to providing innovative digital capabilities and services. In line with this, conventional business models (e.g., finance, transportation, and accommodation industries) are being challenged by digital innovation. However, it is still unclear how the digital innovation (i.e. digital product innovation and digital business model innovation) interact and make sense to focal stakeholders (i.e., consumers, regulators, industrial competitors and partners). Therefore, it is necessary to collect a large volume of data on multiple organizations and various industries engaging in both production and business model innovation. To make it work, advanced information technologies (i.e. Text Mining, Machine Learning, Natural Language Processing, and Deep Learning) enable us to gather and analyze large textual dataset. This also allows us to utilize quantitative methods (e.g., econometrics modeling and data mining) to understand qualitative (and unstructured) data. Combining rich data and quantitative approaches is expected to help us to better comprehend the dynamics in related industries. As a result, my dissertation works is expected to provide both theoretical and methodological contributions to management and digital innovation literatures. Doctor of Philosophy 2020-02-06T06:17:12Z 2020-02-06T06:17:12Z 2020 Thesis-Doctor of Philosophy Zhang, N. (2020). Making sense of digital innovation. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/136949 10.32657/10356/136949 en This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Business::Information technology::Management of information systems
spellingShingle Business::Information technology::Management of information systems
Zhang, Nila
Making sense of digital innovation
description The rapid development of digital technologies has been reshaping the way of designing products, services, and business models by stimulating remarkable innovations to industries. Specifically, the paradigm of production in digital products has shifted from merely increasing hardware parameters to providing innovative digital capabilities and services. In line with this, conventional business models (e.g., finance, transportation, and accommodation industries) are being challenged by digital innovation. However, it is still unclear how the digital innovation (i.e. digital product innovation and digital business model innovation) interact and make sense to focal stakeholders (i.e., consumers, regulators, industrial competitors and partners). Therefore, it is necessary to collect a large volume of data on multiple organizations and various industries engaging in both production and business model innovation. To make it work, advanced information technologies (i.e. Text Mining, Machine Learning, Natural Language Processing, and Deep Learning) enable us to gather and analyze large textual dataset. This also allows us to utilize quantitative methods (e.g., econometrics modeling and data mining) to understand qualitative (and unstructured) data. Combining rich data and quantitative approaches is expected to help us to better comprehend the dynamics in related industries. As a result, my dissertation works is expected to provide both theoretical and methodological contributions to management and digital innovation literatures.
author2 Sia Siew Kien
author_facet Sia Siew Kien
Zhang, Nila
format Thesis-Doctor of Philosophy
author Zhang, Nila
author_sort Zhang, Nila
title Making sense of digital innovation
title_short Making sense of digital innovation
title_full Making sense of digital innovation
title_fullStr Making sense of digital innovation
title_full_unstemmed Making sense of digital innovation
title_sort making sense of digital innovation
publisher Nanyang Technological University
publishDate 2020
url https://hdl.handle.net/10356/136949
_version_ 1789483049839230976