User Experience Modeling and Simulation for Product Ecosystem Design Based on Fuzzy Reasoning Petri Nets

Product ecosystem design entails complex user experience (UX) that involves interactions among multiple users, products, and the ambience. This paper aims to capture causal relationships between UX and design elements and in turn to provide decision support to product ecosystem analysis. A fuzzy reasoning Petri net is developed to deal with the uncertainty, complexity, and dynamics associated with UX modeling. Reasoning of diverse constructs of UX is embedded in the fuzzy production rules that are derived from self-report UX data based on rough set mining. A fuzzy reasoning algorithm is implemented to perform parallel inference by multicriteria rules and to simulate most likely UX under different ambient factors. A case study of subway station UX design demonstrates the potential of product ecosystem FRPN formulation.

[1]  Tom Carey,et al.  ACM SIGCHI Curricula for Human-Computer Interaction , 1992 .

[2]  Dianne Cyr,et al.  Design aesthetics leading to m-loyalty in mobile commerce , 2006, Inf. Manag..

[3]  P. Jordan Designing Pleasurable Products: An Introduction to the New Human Factors , 2000 .

[4]  Jon D. Morris,et al.  The Power of Affect: Predicting Intention , 2002, Journal of Advertising Research.

[5]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[6]  Mitchell M. Tseng,et al.  Design for mass personalization , 2010 .

[7]  Christine L. Lisetti,et al.  MAUI: a multimodal affective user interface , 2002, MULTIMEDIA '02.

[8]  MengChu Zhou,et al.  Fuzzy-Petri-net-based disassembly planning considering human factors , 2006, IEEE Trans. Syst. Man Cybern. Part A.

[9]  Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[10]  G. Clore,et al.  On the interdependence of cognition and emotion , 2007, Cognition & emotion.

[11]  James P. Turley,et al.  The significance of cognitive modeling in building healthcare interfaces , 2006, Int. J. Medical Informatics.

[12]  Suresh K. Nair,et al.  Near optimal solutions for product line design and selection: beam search heuristics , 1995 .

[13]  Raymond Cuninghame-Green,et al.  Bases in max-algebra , 2004 .

[14]  Paul van Schaik,et al.  Modelling user experience - An agenda for research and practice , 2010, Interact. Comput..

[15]  Marc Hassenzahl,et al.  The Interplay of Beauty, Goodness, and Usability in Interactive Products , 2004, Hum. Comput. Interact..

[16]  M. Ashcraft Math Anxiety: Personal, Educational, and Cognitive Consequences , 2002 .

[17]  John Zimmerman,et al.  Measuring the dynamics of remembered experience over time , 2010, Interact. Comput..

[18]  Heshan Sun,et al.  Affective Quality and Cognitive Absorption: Extending Technology Acceptance Research , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[19]  Paul van Schaik,et al.  Modelling user experience with web sites: Usability, hedonic value, beauty and goodness , 2008, Interact. Comput..

[20]  Roger Jianxin Jiao,et al.  A Kansei mining system for affective design , 2006, Expert Syst. Appl..

[21]  Hendrik N.J. Schifferstein,et al.  INTRODUCING PRODUCT EXPERIENCE , 2008 .

[22]  B. Joseph Pine,et al.  The Experience Economy , 2020, Journal of Orthopaedic Experience & Innovation.

[23]  C. V. Negoiţă,et al.  Expert systems and fuzzy systems , 1985 .

[24]  Marc Hassenzahl,et al.  User experience - a research agenda , 2006, Behav. Inf. Technol..

[25]  MengChu Zhou,et al.  Intelligent decision making in disassembly process based on fuzzy reasoning Petri nets , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[26]  Halimahtun M. Khalid,et al.  Affective and Pleasurable Design , 2006 .

[27]  Emilie M. Roth,et al.  Uncovering the Requirements of Cognitive Work , 2008, Hum. Factors.

[28]  Witold Pedrycz,et al.  A generalized fuzzy Petri net model , 1994, IEEE Trans. Fuzzy Syst..

[29]  Eugene H. Melan Process Management: Methods for Improving Products and Service , 1992 .

[30]  Eric Horvitz,et al.  Experience sampling for building predictive user models: a comparative study , 2008, CHI.

[31]  R. Bagozzi,et al.  On the nature and direction of relationships between constructs and measures. , 2000, Psychological methods.

[32]  Victor R. L. Shen,et al.  Supervised and Unsupervised Learning by Using Petri Nets , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[33]  Qianli Xu,et al.  Fundamentals of product ecosystem design for user experience , 2011 .

[34]  Sarah Diefenbach,et al.  Needs, affect, and interactive products - Facets of user experience , 2010, Interact. Comput..

[35]  J. Russell Core affect and the psychological construction of emotion. , 2003, Psychological review.

[36]  Virpi Roto,et al.  Understanding, scoping and defining user experience: a survey approach , 2009, CHI.

[37]  Spyros Tzafestas,et al.  Petri Net-Based Approach to Synthesis of Intelligent Control Systems for DEDS , 1997 .

[38]  MengChu Zhou,et al.  Fuzzy reasoning Petri nets , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[39]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[40]  Jun Du,et al.  Analytical affective design with ambient intelligence for mass customization and personalization , 2007 .

[41]  Marcin S. Szczuka,et al.  The Rough Set Exploration System , 2005, Trans. Rough Sets.