层次分析法向Likert加权测度法的尺度转换——环境意识与品牌资产分析

Siddharth Misra, R. Panda
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引用次数: 4

摘要

跨学科研究在数据分析、解释和决策应用的各个领域都具有相关性。重要变量的选择以及标准导致了研究人员对定量数据的巨大依赖。决策时在量表之间选择的灵活性,开创了量表翻译的新时代。这也有助于研究人员减少他们在数据收集过程中所付出的努力。它需要更多的专业知识来选择适当的工具和尺度来衡量变量及其影响。为此,这项工作试图将用于层次分析法(AHP)的Saaty的9分量表转换为用于排名的广义Likert量表。层次分析法(AHP)是一种适用于决策过程变量排序的多准则决策模型。但是层次分析法是一种非常复杂的技术,涉及到很高的计算能力。本文试图降低计算能力,并采用了一种新的模型,即Likert重量测量方法(LWMM),这种轻量级模型被广泛接受。在心理测量反馈中,LWMM是一种普遍建立的缩放技术,在这种情况下,它已被用于优先考虑环境意识属性和活动,以提高品牌资产。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scale transformation of analytical hierarchy process to Likert weighted measurement method: an analysis on environmental consciousness and brand equity
The interdisciplinary research has found relevance in every field of data analysis, interpretation and decision making applications. The choice of important variables along with the criteria gives rise to the immense reliance of the researchers on quantitative data. The flexibility of choosing between scales for decision making, give rise to a new era of translation of scales. It also aids the researcher to reduce their efforts put in the data collection process. It needs more expertise to select the appropriate tool and scales for measuring the variables and their impact. For this purpose this piece of work is an attempt to convert Saaty's 9 point scale used for analytical hierarchy process (AHP) to a generalised Likert scale for ranking. Analytical hierarchy process (AHP) is an appropriate multicriteria decision making model, which suits the prioritising of variables for decision making process. But AHP is a much complex technique and involves the high computational ability. This research article attempts to reduce the computational ability, and adopts a novel model known as a Likert weight measurement method (LWMM), this lightweight model is widely accepted. In psychometric feedback LWMM is universally established scaling technique and in this case has been used to prioritise environmental conscious attributes and activities for improving brand equity.
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