英文摘要 |
When investigating the semantics projected by product forms, researchers often use the semantic differential method with bipolar adjectives, such as 'modern-classical' or 'simple-complex'. The image projected by a product is assumed to center somewhere in the continuum between the two opposite adjectives. However, in design practice, some design examples clearly exhibit the simultaneous use of contradictory meanings in product semantics. For example, retro cars evoke nostalgia by borrowing characteristics from classical cars, but at the same time exhibit modernness. In this research, we examined the results of applying the semantic differential method to measure contradiction in product semantics. Then, the results were verified by direct measurement method, which is developed from attitudinal ambivalence research. Our results showed that the distributions of semantic differential ratings for the stimuli with contradictory meanings have higher standard deviations. Further analysis indicated that these distributions deviate from the (symmetric) normal distribution with negative kurtosis value. In addition, we found that the 'novelty-in-typicality' chairs are likely to have prototypical shapes with additional functions or embedded stories, and that the 'simple yet complex' chairs are achieved through the use of material, texture, and complicated product forms. In general, successful embedding of contradictory meanings into product forms are based on simple, typical, and rational forms that are made to simultaneously exhibit complex, novel, and emotional images by introducing additional elements. This means that, for stimuli with contradictory meanings in product semantics, the usual implicit assumption that the image projected by a product form is centered somewhere between a pair of opposite adjectives, and that the ratings follow the normal distribution, does not hold. Large standard deviations in semantic differential ratings can be used to roughly filter out products with possible contradictory meanings. The reasons for relatively large standard deviation can result from three possible reasons, including contradiction, insensitivity, and differences between groups. Thus, a further analysis of distribution or a direct measurement method is needed to better measure the potential contradictory responses towards products. |