• Title/Summary/Keyword: Attribute resemblance

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Attribute Resemblance and Preference for Products: Moderating Effect of Attribute Familiarity

  • Kwanho Suk
    • Asia Marketing Journal
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    • v.25 no.1
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    • pp.3-14
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    • 2023
  • This research examines how consumer preferences for products are affected by attribute resemblance, which refers to the degree to which a product is similar with other products that are being evaluated together. It is expected that the influence of attribute resemblance on attitude and choice is moderated by attribute familiarity, which is tested in three empirical studies. Studies 1 and 2 examine the effects on the attitude toward the product and show that the positive influence of attribute resemblance on attitude is stronger when attribute are less (vs. more) familiar. Study 3 tests the effects on choice for which attribute resemblance can have a negative influence because of the increase in the competition with similar options. For choice, the attribute resemblance has a positive influence when attributes are less familiar but has a negative influence when attributes are more familiar.

The application of a digital relief model to landform classification (LANDFORM 분류를 위한 수치기복모형의 적용)

  • Yang, In-Tae;Kim, Dong-Moon;Yu, Young-Geol;Chun, Ki-Sun
    • Journal of Industrial Technology
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    • v.19
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    • pp.155-162
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    • 1999
  • In the last few years the automatic classification of morpholgical landforms using GSIS and DEM was investigated. Particular emphasis has been put on the morphological point attribute approaches and the extraction of drainage basin variables from digital elevation models. The automated derivation of landforms has become a neccessity for quantitative analysis in geomorphology. Furthermore, the application of GSIS technologies has become an important tool for data management and numerical data analysis for purpose of geomorphological mapping. A process developed by Dikau et al, which automates Hanmond's manual process, was applied to the pyoung chang of the kangwon. Although it produced a classification that has good resemblance to the landforms in the area, it had some problems. For example, it produced a progressive zonation when landform changes from plains to mountains, it does not distinguish open valleys from a plains mountain interface, and it was affected by micro relief. Although automating existing quantitative manual processes is an important step in the evolution automation, definition may need to be calibrated since the attributes are oftem measured differently. A new process is presented that partly solves these problems.

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