Smart nudging: How cognitive technologies enable choice architectures for value co-creation

Mele, Cristina; Spena, Tiziana Russo; Kaartemo, Valtteri; Marzullo, Marialuisa

doi:10.1016/j.jbusres.2020.09.004

Cited by 95 publications

(76 citation statements)

References 57 publications

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“…Two enhanced value co-creation practices emerge: empowering actors in medical care and engaging actors in a healthy lifestyle. The boundary work of actors lies in a smarter resource integration that yields broader applications for augmented agency (Mele et al, 2021).…”

Section: Boundary Work In Value Co-creation Practicesmentioning

confidence: 99%

Boundary work in value co-creation practices: the mediating role of cognitive assistants

Mele

Spena

Marzullo

et al. 2021

JOSM

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PurposeHow to improve healthcare for the ageing population is attracting academia attention. Emerging technologies (i.e. robots and intelligent agents) look relevant. This paper aims to analyze the role of cognitive assistants as boundary objects in value co-creation practices. We include the perceptions of the main actors – patients, (in)formal caregivers, healthcare professionals – for a fuller network perspective to understand the potential overlap between boundary work and value co-creation practices.Design/methodology/approachWe adopted a grounded approach to gain a contextual understanding design to effectively interpret context and meanings related to human–robot interactions. The study context concerns 21 health solutions that had embedded the Watson cognitive platform and its adoption by the youngest cohort (50–64-year-olds) of the ageing population.FindingsThe cognitive assistant acts as a boundary object by bridging actors, resources and activities. It enacts the boundary work of actors (both ageing and professional, caregivers, families) consisting of four main actions (automated dialoguing, augmented sharing, connected learning and multilayered trusting) that elicit two ageing value co-creation practices: empowering ageing actors in medical care and engaging ageing actors in a healthy lifestyle.Originality/valueWe frame the role of cognitive assistants as boundary objects enabling the boundary work of ageing actors for value co-creation. A cognitive assistant is an “object of activity” that mediates in actors' boundary work by offering novel resource interfaces and widening resource access and resourceness. The boundary work of ageing actors lies in a smarter resource integration that yields broader applications for augmented agency.

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Section: Boundary Work In Value Co-creation Practicesmentioning

confidence: 99%

Boundary work in value co-creation practices: the mediating role of cognitive assistants

Mele

Spena

Marzullo

et al. 2021

JOSM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Information service points are used to make alternative decisions, both mobile and non-mobile devices to access sensors, intelligent interaction systems, etc. to enable systematic use of smart spaces [21]. There is also a need to think about existing ecosystems such as cultures, communities or organizations to make the connection.…”

Section: Intelligent Interactive Learning Platformmentioning

confidence: 99%

“…In many studies there are components for intelligent space applications, for example, Mele et al [21] researched on the use of cognitive technologies to create alternative architectures for value Co-Creation, in the construct architecture, it analyzes the following as: internet signal, access point and data service point used to make alternative decisions. Both mobile and stationary devices are used to access sensors, intelligent interaction systems, etc.…”

Section: Intelligent Interactive Learning Platformmentioning

confidence: 99%

Intelligent Interactive Learning Platform for Seamless Learning Ecosystem to Enhance Digital Citizenship’s Lifelong Learning

Pornpongtechavanich

Wannapiroon

2021

Int. J. Emerg. Technol. Learn.

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The purpose of this research is to: 1) synthesize documents and international research of intelligent interactive learning platforms for seamless learning ecosystems to enhance citizens’ lifelong digital learning 2) design an intelli-gent interactive learning platform for a seamless learning ecosystem to en-hance citizens’ lifelong digital learning 3) assess the suitability of the intelligent interactive learning platform for seamless learning ecosystem. Ten experts were selected. They had to have had more than five years of relevant experience in the field consisting of expertise in System. Architec-ture, intelligent learning platforms, seamless learning ecosystems and citi-zens’ lifelong digital learning. The research instruments were a suitability as-sessment form for an intelligent interactive learning platform for seam-less learning ecosystems to enhance citizens’ lifelong digital learning. The results of this research found that the intelligent interactive learning plat-form for a seamless learning ecosystem to enhance citizens’ lifelong digital learning, was developed and it was appropriate.

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“…In [25], People decide and take everyday measures to better their livelihoods and turn more to the Artificial intelligence Approach (AIA) to help them decide. Such developments indicate how AI and other cognitive technologies impact the co-creation of value.…”

Section: Introduction Of Cognitive Computing Framework For Smart Decisionmentioning

confidence: 99%

Cognitive Computing Integrated Methodology For Smart Decision Making And Problem-Solving

Liu¹

2021

Preprint

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Cognitive computing is the field of intelligent computational study that imitates the brain process for computational intelligence. Decision-making is part of the cognitive process in which opportunities based on certain criteria are selected for a course of action. The choice is generally made using the intelligent assistance system that can turn human decision-making into Artificial Intelligence, system engineering, machine learning approaches. Many complicated real-world problems have been solved by the desire to replicate human intelligence into robots and progress in artificial intelligent technologies. Autonomous systems with machine cognition continuously develop by using enormous data volume and processing power. The cognitive computing system uses skill and awareness derived from knowledge and intelligent decision-making. In this paper, the cognitive computing-based human speech recognition framework (CC-HSRF) takes advantage of next-generation technologies to assist smart decision-making effectively. The proposed methods overview cognitive calculation and its historical perspectives, followed by several strategies to implement algorithms for intelligent decision-making using machine learning. Methods for effective knowledge processing are explored based on cognitive computing models such as Object-Attribute-Relation (OAR). It offers visual and cognitive analytics information, highlighting the framework of conceptual vision and its difficulties. This framework aims to increase the quality of artificial intelligent decision-making based on human perceptions, comprehensions, and actions to reduce business mistakes in the real world and ensure right, accurate, informed, and timely human decisions.

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Smart nudging: How cognitive technologies enable choice architectures for value co-creation

Cited by 95 publications

References 57 publications

Boundary work in value co-creation practices: the mediating role of cognitive assistants

Boundary work in value co-creation practices: the mediating role of cognitive assistants

Intelligent Interactive Learning Platform for Seamless Learning Ecosystem to Enhance Digital Citizenship’s Lifelong Learning

Cognitive Computing Integrated Methodology For Smart Decision Making And Problem-Solving

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