Developing smart service concepts: morphological analysis using a Novelty-Quality map

Han, Mintak; Park, Yongtae

doi:10.1080/02642069.2018.1548616

Cited by 5 publications

(2 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Text mining is used to support the building of morphological analysis, text-driven morphological analysis, c.f. [15,96,99]. Geum et al used sensor data to generate ideas [97].…”

Section: Summary Of Identified Idea Generation Techniques Using Idea ...mentioning

confidence: 99%

A Systematic Literature Review about Idea Mining: The Use of Machine-Driven Analytics to Generate Ideas

Ayele

Juell-Skielse

2021

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Idea generation is the core activity of innovation. Digital data sources, which are sources of innovation, such as patents, publications, social media, websites, etc., are increasingly growing at unprecedented volume. Manual idea generation is time-consuming and is affected by the subjectivity of the individuals involved. Therefore, the use machine-driven data analytics techniques to analyze data to generate ideas and support idea generation by serving users is useful. The objective of this study is to study state-of the-art machine-driven analytics for idea generation and data sources, hence the result of this study will generally serve as a guideline for choosing techniques and data sources. A systematic literature review is conducted to identify relevant scholarly literature from IEEE, Scopus, Web of Science and Google Scholar. We selected a total of 71 articles and analyzed them thematically. The results of this study indicate that idea generation through machine-driven analytics applies text mining, information retrieval (IR), artificial intelligence (AI), deep learning, machine learning, statistical techniques, natural language processing (NLP), NLP-based morphological analysis, network analysis, and bibliometric to support idea generation. The results include a list of techniques and procedures in idea generation through machine-driven idea analytics. Additionally, characterization and heuristics used in idea generation are summarized. For the future, tools designed to generate ideas could be explored.

show abstract

“…Text mining is used to support the building of morphological analysis, text-driven morphological analysis, c.f. [15,96,99]. Geum et al used sensor data to generate ideas [97].…”

Section: Summary Of Identified Idea Generation Techniques Using Idea ...mentioning

confidence: 99%

A Systematic Literature Review about Idea Mining: The Use of Machine-Driven Analytics to Generate Ideas

Ayele

Juell-Skielse

2021

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

show abstract

“…Furthermore, service ecosystems have been confused with networks (McColl‐Kennedy et al., 2012) and understood from different theoretical positions (Adner, 2017; Autio & Thomas, 2020). The confusion is even more pronounced as service systems continue to be reframed in novel ways, such as smart service systems (Han & Park, 2019), healthcare service systems (Anderson et al., 2019), human‐centred service systems (Huetten et al., 2019), and public service systems (Eriksson et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

The evolution of service systems to service ecosystems: A literature review

Brozović

Tregua

2022

Int J Management Reviews

View full text Add to dashboard Cite

High academic interest and numerous theoretical and practical studies on service systems and service ecosystems, paired with the accelerated evolution of the service (eco) system concept, have resulted in complex research in this field. Multiple perspectives from which service systems were studied added to this complexity and inadvertently produced conceptual confusion regarding service (eco) systems. This literature review addresses this confusion by focusing on the evolution of service systems to service ecosystems to consolidate and clarify the field. Therefore, this article's purpose is to systematise the extant research on service (eco) systems and indicate future research directions based on the analysis. Specifically, the article systematically reviews 770 publications on service (eco) systems from 2020 and earlier and identifies the main research topics (focusing on service [eco] systems' constituent elements, inherent processes, and outcomes), theoretical perspectives, and bridging elements, and suggests future research based on the review results. The article concludes by providing a foundation for continued research emerging from the analysis, with emphasis on five aspects that may stimulate new avenues of research: service ecospheres, service ecosystem simplicity, failures of service ecosystems, paradox in service ecosystems, and panarchy and service ecosystems.

show abstract

State of the Art of Smart Services Research – Applications and Customer Acceptance

Madlberger

2022

Forum Dienstleistungsmanagement

View full text Add to dashboard Cite

Developing smart service concepts: morphological analysis using a Novelty-Quality map

Cited by 5 publications

References 39 publications

A Systematic Literature Review about Idea Mining: The Use of Machine-Driven Analytics to Generate Ideas

A Systematic Literature Review about Idea Mining: The Use of Machine-Driven Analytics to Generate Ideas

The evolution of service systems to service ecosystems: A literature review

State of the Art of Smart Services Research – Applications and Customer Acceptance

Contact Info

Product

Resources

About