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Petri Net-Based Affective-Cognitive Modeling for Product Ecosystem Design

Authors: Qianli Xu; Feng Zhou; Jianxin Roger Jiao;

Petri Net-Based Affective-Cognitive Modeling for Product Ecosystem Design

Abstract

Product ecosystem design that emphasizes user experience (UX) with both users’ affective and cognitive aspects lends itself to be of primary importance to value-added user satisfaction. In a product ecosystem, there are human users, multiple products, and the ambience. Thus it involves complex human-product-ambience interactions, which contribute to UX evolution with its ambiguous affective states in conjunction with the cognitive process. In order to optimize UX in the context of product ecosystems, this paper formulates the architecture of product ecosystems with a particular focus on event-driven UX. Further, the causal relations embedded in users’ affective perception and cognitive processes are modeled by a technique called colored dynamic fuzzy Petri net. A subway station design is exemplified to illustrate the proposed methodology. Preliminary results by simulation show the potential and feasibility of the proposed method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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