Gift flowers should be chosen to depict a message with the sender's kansei and are bound by nature of flowers and social manners, to maintain social relationship between…
Gift flowers should be chosen to depict a message with the sender's kansei and are bound by nature of flowers and social manners, to maintain social relationship between the sender and the recipient. Few buyers, but most florists, have expert knowledge of the flowering time, scent, price, and nature of each flower, and are experts in arranging flowers that meet a given purpose. The purpose of this paper is to incorporate handling constraints into the inference process of a kansei engineering system.
The paper collected the expert knowledge concerning nature of flowers, composing flower arrangements and social manners on gifts from specialists of flower arrangements including a florist and special books. At the same time, kansei evaluation experiments on the kinds of flowers and colors were conducted. The expertise and the results of kansei experiments were organized into a flower database and inference rules for choice of a main flower, arrangement shapes and combination flowers. The rules were implemented as server‐side programs. Users input information about the recipient, purpose of the arrangement and purchase information using a web browser. The system outputs a solution; a list of main flowers, combination flowers, greens and the shape of arrangement.
Traditional kansei engineering studies revealed the relationships between design elements and kansei with developing new analyzing methods. Different constraints come into the actual product design and manufacturing should be integrated with findings obtained from the kansei evaluation to successfully utilize kansei engineering for product development.
The inference rules will be able to tell the reasons for choosing the main‐ and combination flowers and arrangement shapes to satisfy the customers.
The proposed system suggests the original arrangement of flowers unlike most online florists selling ready‐made arrangements. The paper shows a solution to incorporate different constraints underlying in a real production process into the inference process based on the result of kansei analysis.
This paper seeks to deal with affective design of waiting areas (servicescapes) and has twofold aims. The first, is to explore affective values for waiting areas. The second, is to identify interactions between physical design attributes and affective values.
This study included a free association method for data collection, applying Kansei engineering methodology to extract design solutions relating to specific feelings. The study was undertaken at six primary health centres in Östergötland County, Sweden. In total, 88 participants (60 patients and 28 staff) were interviewed.
The selected waiting areas show significant differences for their perceived affective qualities. The most desired feeling for creating affective values is found to be “calm”. The core design attributes contributing to this feeling are privacy, colours, child play‐areas and green plants. Good design of lighting, seating arrangements and a low sound level are also important design attributes to give a more complete design solution.
The study provides useful insights for understanding affective needs in servicescapes, and it provides design suggestions. The results have not been analysed separately for gender or different age groups.
The paper proposes a framework model to be applied when dealing with affective values in servicescapes.
This paper makes an original contribution to understand affective values towards the physical environment in servicescape design. It offers a methodology to study complex environments with many alternative design solutions using limited resources. Moreover, this study uses a combination of a free association method and Rough Sets theory in affective design.