Values, Susceptibility to Normative Influence, and Attribute Importance Weights: A Nomological Analysis
نویسندگان
چکیده
منابع مشابه
Attribute Importance Weights in Conjoint Analysis: Bias and Pr
ATTRIBUTE IMPORTANCE WEIGHTS IN CONJOINT ANALYSIS: BIAS AND PRECISION Sanjay Mishra, Washington State University U. N. Umesh, Washington State University Donald E. Stem, Jr., Washington State University ABSTRACT Consumer researchers have used conjoint analysis to evaluate the importance of an attribute in forming preferences. Although past researchers have tested the validity and reliability of...
متن کاملA subjective and objective integrated approach to determine attribute weights
This paper proposes an integrated approach to determine attribute weights in the multiple attribute decision making problems. The approach makes use of the subjective information provided by a decision maker and the objective information to form a two-objective programming model. Thus the resultant attribute weights and rankings of alternatives reflect both the subjective considerations of a de...
متن کاملBiological adaptation and normative values.
The occlusal interface is often considered in terms of a structural entity, and to reflect several structural components of the masticatory system: alveolar and cranial bone, the tem-poromandibular joint (TMJ) including its disc and associated ligaments, the dentition (both pulp and periodontium), and the masticatory muscles (including ligaments and tendons and other connective tissues as well ...
متن کاملPrioritising, Ranking and Resource Implementation - A Normative Analysis
Background Priority setting in publicly financed healthcare systems should be guided by ethical norms and other considerations viewed as socially valuable, and we find several different approaches for how such norms and considerations guide priorities in healthcare decision-making. Common to many of these approaches is that interventions are ranked in relation to each other, following the appli...
متن کاملUnsupervised learning of prototypes and attribute weights
In this paper, we introduce new algorithms that perform clustering and feature weighting simultaneously and in an unsupervised manner. The proposed algorithms are computationally and implementationally simple, and learn a di1erent set of feature weights for each identi2ed cluster. The cluster dependent feature weights o1er two advantages. First, they guide the clustering process to partition th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Consumer Psychology
سال: 2001
ISSN: 1532-7663,1057-7408
DOI: 10.1207/153276601750408348