Abstract
Gathering customer data over the Internet is largely limited to collecting the responses to a set of easily answerable questions, such as Yes/No questions and Likert scale questions. These data are then analyzed to identify customer trends or other items of interest to management. The data can be useful but key to their usage is the application of suitable mathematical tools. Traditionally little more than standard statistics has been used in the analysis of ordinal, or category, data. This can be inaccurate and in some cases, misleading. This paper introduces measures of agreement and dissent to the field of eBusiness analysis and shows how ordinal data can be analyzed in more meaningful ways.
| Original language | English |
|---|---|
| Pages (from-to) | 16-25 |
| Number of pages | 10 |
| Journal | International Journal of e-Business Research |
| Volume | 4 |
| Issue number | 4 |
| State | Published - 2008 |
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All Science Journal Classification (ASJC) codes
- Management Information Systems
- Computer Science Applications
Cite this
E-business decision making by agreement. / Tastle, William J.; Wierman, Mark J.
In: International Journal of e-Business Research, Vol. 4, No. 4, 2008, p. 16-25.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - E-business decision making by agreement
AU - Tastle, William J.
AU - Wierman, Mark J.
PY - 2008
Y1 - 2008
N2 - Gathering customer data over the Internet is largely limited to collecting the responses to a set of easily answerable questions, such as Yes/No questions and Likert scale questions. These data are then analyzed to identify customer trends or other items of interest to management. The data can be useful but key to their usage is the application of suitable mathematical tools. Traditionally little more than standard statistics has been used in the analysis of ordinal, or category, data. This can be inaccurate and in some cases, misleading. This paper introduces measures of agreement and dissent to the field of eBusiness analysis and shows how ordinal data can be analyzed in more meaningful ways.
AB - Gathering customer data over the Internet is largely limited to collecting the responses to a set of easily answerable questions, such as Yes/No questions and Likert scale questions. These data are then analyzed to identify customer trends or other items of interest to management. The data can be useful but key to their usage is the application of suitable mathematical tools. Traditionally little more than standard statistics has been used in the analysis of ordinal, or category, data. This can be inaccurate and in some cases, misleading. This paper introduces measures of agreement and dissent to the field of eBusiness analysis and shows how ordinal data can be analyzed in more meaningful ways.
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UR - http://www.scopus.com/inward/citedby.url?scp=49249105915&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:49249105915
VL - 4
SP - 16
EP - 25
JO - International Journal of e-Business Research
JF - International Journal of e-Business Research
SN - 1548-1131
IS - 4
ER -