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.
| Original language | English |
|---|---|
| Pages (from-to) | 7040-7044 |
| Number of pages | 5 |
| Journal | Expert Systems with Applications |
| Volume | 36 |
| Issue number | 3 PART 2 |
| DOIs | |
| Publication status | Published - 2009 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Engineering(all)
- Computer Science Applications
- Artificial Intelligence
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The development of a confidence interval-based importance-performance analysis by considering variability in analyzing service quality. / Wu, Hsin-Hung; Shieh, Jiunn I.
In: Expert Systems with Applications, Vol. 36, No. 3 PART 2, 01.01.2009, p. 7040-7044.Research output: Contribution to journal › Article
TY - JOUR
T1 - The development of a confidence interval-based importance-performance analysis by considering variability in analyzing service quality
AU - Wu, Hsin-Hung
AU - Shieh, Jiunn I.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=58349108668&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58349108668&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2008.08.055
DO - 10.1016/j.eswa.2008.08.055
M3 - Article
AN - SCOPUS:58349108668
VL - 36
SP - 7040
EP - 7044
JO - Expert Systems with Applications
JF - Expert Systems with Applications
SN - 0957-4174
IS - 3 PART 2
ER -