Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support

Jani Kinnunen; Mikael Collan; Irina Georgescu; Zahra Hosseini

doi:10.1007/978-3-030-90963-5_35

Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support

Jani Kinnunen
, Mikael Collan
, Irina Georgescu^*
, Zahra Hosseini

^*Korresponderande författare för detta arbete

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

5 Citeringar (Scopus)

Sammanfattning

Digitalization and artificial intelligence are growing in importance as parts of decision-support tools in various application domains. One of the important developments in this vein has been the creation of interactive tools for coaching users of complex decision-support systems to help them successfully and correctly use the said systems. This paper focuses on digital coaching in the context of strategic investment analysis, specifically connected to fuzzy real options analysis (ROA). We present some important and difficult choices connected to ROA and discuss how digital coaching may assist users in better using ROA tools. We illustrate the real-world use of digital coaching in the contexts of cash-flow evaluation with machine learning support and aggregation of cash-flows from multiple experts. The discussion and the cases illustrate well how digital coaching can make a difference, especially for an inexperienced user, in guiding users to use complex tools correctly and in creating better circumstances for credible analyses. The findings presented are new and contribute specifically to the literature on digital coaching and real options analysis.

Originalspråk	Engelska
Titel på värdpublikation	HCI International 2021 - Late Breaking Papers
Undertitel på värdpublikation	Multimodality, eXtended Reality, and Artificial Intelligence
Redaktörer	Constantine Stephanidis, Masaaki Kurosu, Jessie Y.C. Chen, Gino Fragomeni, Norbert Streitz, Shin’ichi Konomi, Helmut Degen, Stavroula Ntoa
Förlag	Springer Science and Business Media Deutschland GmbH
Sidor	455-473
Antal sidor	19
ISBN (tryckt)	9783030909628
DOI	https://doi.org/10.1007/978-3-030-90963-5_35
Status	Publicerad - 2021
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	23rd International Conference on Human-Computer Interaction, HCII 2021 - Virtual, Online Varaktighet: 24 juli 2021 → 29 juli 2021

Publikationsserier

Namn	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volym	13095 LNCS
ISSN (tryckt)	0302-9743
ISSN (elektroniskt)	1611-3349

Konferens

Konferens	23rd International Conference on Human-Computer Interaction, HCII 2021
Ort	Virtual, Online
Period	24/07/21 → 29/07/21

Finansiering

Acknowledgements. This research is supported by the Finnish Strategic Research Council at the Academy of Finland project Manufacturing 4.0 grants 335980 and 335990.

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10.1007/978-3-030-90963-5_35

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Kinnunen, J., Collan, M., Georgescu, I., & Hosseini, Z. (2021). Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support. I C. Stephanidis, M. Kurosu, J. Y. C. Chen, G. Fragomeni, N. Streitz, S. Konomi, H. Degen, & S. Ntoa (Red.), HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence (s. 455-473). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13095 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-90963-5_35

Kinnunen, Jani ; Collan, Mikael ; Georgescu, Irina et al. / Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support. HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence . redaktör / Constantine Stephanidis ; Masaaki Kurosu ; Jessie Y.C. Chen ; Gino Fragomeni ; Norbert Streitz ; Shin’ichi Konomi ; Helmut Degen ; Stavroula Ntoa. Springer Science and Business Media Deutschland GmbH, 2021. s. 455-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support",

abstract = "Digitalization and artificial intelligence are growing in importance as parts of decision-support tools in various application domains. One of the important developments in this vein has been the creation of interactive tools for coaching users of complex decision-support systems to help them successfully and correctly use the said systems. This paper focuses on digital coaching in the context of strategic investment analysis, specifically connected to fuzzy real options analysis (ROA). We present some important and difficult choices connected to ROA and discuss how digital coaching may assist users in better using ROA tools. We illustrate the real-world use of digital coaching in the contexts of cash-flow evaluation with machine learning support and aggregation of cash-flows from multiple experts. The discussion and the cases illustrate well how digital coaching can make a difference, especially for an inexperienced user, in guiding users to use complex tools correctly and in creating better circumstances for credible analyses. The findings presented are new and contribute specifically to the literature on digital coaching and real options analysis.",

keywords = "Decision-support, Digital coaching, Machine learning, Real options, Strategic investments",

author = "Jani Kinnunen and Mikael Collan and Irina Georgescu and Zahra Hosseini",

note = "Funding Information: Acknowledgements. This research is supported by the Finnish Strategic Research Council at the Academy of Finland project Manufacturing 4.0 grants 335980 and 335990. Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 23rd International Conference on Human-Computer Interaction, HCII 2021 ; Conference date: 24-07-2021 Through 29-07-2021",

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pages = "455--473",

editor = "Constantine Stephanidis and Masaaki Kurosu and Chen, \{Jessie Y.C.\} and Gino Fragomeni and Norbert Streitz and Shin{\textquoteright}ichi Konomi and Helmut Degen and Stavroula Ntoa",

booktitle = "HCI International 2021 - Late Breaking Papers",

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Kinnunen, J, Collan, M, Georgescu, I & Hosseini, Z 2021, Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support. i C Stephanidis, M Kurosu, JYC Chen, G Fragomeni, N Streitz, S Konomi, H Degen & S Ntoa (red), HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13095 LNCS, Springer Science and Business Media Deutschland GmbH, s. 455-473, 23rd International Conference on Human-Computer Interaction, HCII 2021, Virtual, Online, 24/07/21. https://doi.org/10.1007/978-3-030-90963-5_35

Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support. / Kinnunen, Jani; Collan, Mikael; Georgescu, Irina et al.
HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence . red. / Constantine Stephanidis; Masaaki Kurosu; Jessie Y.C. Chen; Gino Fragomeni; Norbert Streitz; Shin’ichi Konomi; Helmut Degen; Stavroula Ntoa. Springer Science and Business Media Deutschland GmbH, 2021. s. 455-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13095 LNCS).

Forskningsoutput: Kapitel i bok/konferenshandling › Publicerad konferensartikel › Vetenskaplig › Peer review

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AU - Georgescu, Irina

AU - Hosseini, Zahra

N1 - Funding Information: Acknowledgements. This research is supported by the Finnish Strategic Research Council at the Academy of Finland project Manufacturing 4.0 grants 335980 and 335990. Publisher Copyright: © 2021, Springer Nature Switzerland AG.

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AB - Digitalization and artificial intelligence are growing in importance as parts of decision-support tools in various application domains. One of the important developments in this vein has been the creation of interactive tools for coaching users of complex decision-support systems to help them successfully and correctly use the said systems. This paper focuses on digital coaching in the context of strategic investment analysis, specifically connected to fuzzy real options analysis (ROA). We present some important and difficult choices connected to ROA and discuss how digital coaching may assist users in better using ROA tools. We illustrate the real-world use of digital coaching in the contexts of cash-flow evaluation with machine learning support and aggregation of cash-flows from multiple experts. The discussion and the cases illustrate well how digital coaching can make a difference, especially for an inexperienced user, in guiding users to use complex tools correctly and in creating better circumstances for credible analyses. The findings presented are new and contribute specifically to the literature on digital coaching and real options analysis.

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KW - Strategic investments

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DO - 10.1007/978-3-030-90963-5_35

M3 - Published conference proceeding

AN - SCOPUS:85119870603

SN - 9783030909628

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Kinnunen J, Collan M, Georgescu I, Hosseini Z. Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support. I Stephanidis C, Kurosu M, Chen JYC, Fragomeni G, Streitz N, Konomi S, Degen H, Ntoa S, redaktörer, HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence . Springer Science and Business Media Deutschland GmbH. 2021. s. 455-473. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-90963-5_35

Digital Coaching System for Real Options Analysis with Multi-expert and Machine Learning Support

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