10,456 research outputs found
Methodology for Designing Decision Support Systems for Visualising and Mitigating Supply Chain Cyber Risk from IoT Technologies
This paper proposes a methodology for designing decision support systems for
visualising and mitigating the Internet of Things cyber risks. Digital
technologies present new cyber risk in the supply chain which are often not
visible to companies participating in the supply chains. This study
investigates how the Internet of Things cyber risks can be visualised and
mitigated in the process of designing business and supply chain strategies. The
emerging DSS methodology present new findings on how digital technologies
affect business and supply chain systems. Through epistemological analysis, the
article derives with a decision support system for visualising supply chain
cyber risk from Internet of Things digital technologies. Such methods do not
exist at present and this represents the first attempt to devise a decision
support system that would enable practitioners to develop a step by step
process for visualising, assessing and mitigating the emerging cyber risk from
IoT technologies on shared infrastructure in legacy supply chain systems
Recommended from our members
Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software, and Other Digital Artifacts
Recommended from our members
Twenty years of technology and strategic roadmapping research: A school of thought perspective
© 2020 Two decades ago the thirtieth-anniversary special issue of Technological Forecasting and Social Change correctly anticipated the widespread adoption of technology and strategic roadmapping at firm, sectoral and national levels. In this article, we explore the evolution of roadmapping studies since that time. Drawing on a mixed-methods approach (i.e. topic modelling, genealogical analysis, content analysis and interviews), we reveal the development of seven distinctive ‘schools of thought’: the Cambridge practical school, the Seoul school, the Portland and Bangkok schools, the Cambridge phenomenological school, the Beijing school and the Moscow school. We show that the schools differ in terms of (a) the research orientation, whether it be solution- or theory-oriented; (b) the research methods and data sources being used; and (c) the nature of contributions that each school seeks to achieve. The different areas of emphasis associated with each school are not competing but complementary, and together they develop the eclectic body of knowledge on roadmapping
Recommended from our members
Text mining analysis roadmap (TMAR) for service research
Purpose
The purpose of this paper is to offer a step-by-step text mining analysis roadmap (TMAR) for service researchers. The paper provides guidance on how to choose between alternative tools, using illustrative examples from a range of business contexts.
Design/methodology/approach
The authors provide a six-stage TMAR on how to use text mining methods in practice. At each stage, the authors provide a guiding question, articulate the aim, identify a range of methods and demonstrate how machine learning and linguistic techniques can be used in practice with illustrative examples drawn from business, from an array of data types, services and contexts.
Findings
At each of the six stages, this paper demonstrates useful insights that result from the text mining techniques to provide an in-depth understanding of the phenomenon and actionable insights for research and practice.
Originality/value
There is little research to guide scholars and practitioners on how to gain insights from the extensive “big data” that arises from the different data sources. In a first, this paper addresses this important gap highlighting the advantages of using text mining to gain useful insights for theory testing and practice in different service contexts.
</jats:sec
- …