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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8723


    Title: The development of a confidence interval-based importance-performance analysis by considering variability in analyzing service quality
    Authors: : Wu, Hsin-Hung;Shieh, Jiunn-I
    Contributors: Department of Information Science and Applications
    Keywords: Financial data processing;Planning;Strategic planning;Confidence interval;Importance-performance analysis;Point estimate;Sampling error;Variability
    Date: 2009
    Issue Date: 2010-04-07 21:34:11 (UTC+8)
    Publisher: Asia University
    Abstract: The traditional importance-performance analysis (IPA) uses the mean ratings of importance and performance to construct a two-dimensional grid by identifying improvement opportunities and guiding strategic planning efforts. The point estimates of importance and performance vary from sample to sample such that the numerical analyses are different based upon different samples. Thus, using point estimates for items might lead the management to make false decisions. This study integrates confidence intervals and IPA to reduce the variability which enables the decision maker much easier to identify the strengths and weaknesses based upon the sample of size used. Moreover, the assumptions of equal and unequal population variances for constructing confidence intervals are discussed. © 2008 Elsevier Ltd. All rights reserved.
    Relation: Expert Systems with Applications 36(3 ) PART 2:7040-7044
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

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