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Factors Affecting The Adoption Of The Personality Of Design
[Les Facteurs Determinants De La Diffusion/Adoption De La Personnalite Du Design]

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  • Valentin Ngadi

    (CEPN - Centre d'Economie de l'Université Paris Nord - UP13 - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique)

Abstract

Through the omnipresence of design and the emergence of new behavior in the market, the customers seek to adopt the personalities of designs to consolidate their specificity in order to build a proper and differentiating identity. The diffusion/adoption of the design personality becomes a necessity for companies or organizations which wish to increase or maintain their market share, and like retaining the customers. However, the diffusion / adoption of the personality of design by the consumers is not something obvious and is not sufficiently explored. The objective is to determine the factors which support the diffusion / adoption of the personality of design. By using the theories of the interpersonal behavior, the reasoned action, the planned behavior, the acceptance of technology, the motivation and the diffusion of innovation, a model of the factors diffusion/adoption of the personality of design was put forward. The results show that the adoption is subordinate to the mix diffusion (the perception of the personality of the design, channels of communication and the personal factors of the individual).These factors can serve as a barometer and a predictive power of the diffusion/adoption of the personality of design by the consumers.

Suggested Citation

  • Valentin Ngadi, 2016. "Factors Affecting The Adoption Of The Personality Of Design [Les Facteurs Determinants De La Diffusion/Adoption De La Personnalite Du Design]," CEPN Working Papers hal-01296338, HAL.
    • Handle: RePEc:hal:cepnwp:hal-01296338
    Note: View the original document on HAL open archive server: https://hal.science/hal-01296338
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    References listed on IDEAS

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    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    5. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
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