Classifying web metrics using the web quality model

Classifying web metrics using the web quality model Purpose – The purpose of this paper is to classify the most important metrics proposed for web information systems, with the aim of offering the user a global vision of the state of the research within this area. Design/methodology/approach – WQM distinguishes three dimensions related to web features, lifecycle processes and quality characteristics. A range of recently published (1992‐2004) works that include web metrics definitions have been studied and classified within this model. Findings – In this work, a global vision of web metrics is provided. Concretely, it was found that about 44 percent of metrics are related to “presentation” and that most metrics (48 percent) are usability metrics. Regarding the life cycle, the majority of metrics are related to operation and maintenance processes. Nevertheless, focusing on metrics validation, it was found that there is not too much work done, with only 3 percent of metrics validated theoretically and 37 percent of metrics validated empirically. Practical implications – The classification presented tries to facilitate the use and application of web metrics for different kinds of stakeholders (developers, maintainers, etc.) as well as to clarify where web metric definition efforts are centred, and thus where it is necessary to focus future works. Originality/value – This work tries to cover a deficiency in the web metrics field, where many proposals have been stated but without any kind of rigour and order. Consequently, the application of the proposed metrics is difficult and risky, and it is dangerous to base decisions on their values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Online Information Review Emerald Publishing

Classifying web metrics using the web quality model

Online Information Review, Volume 29 (3): 22 – Jun 1, 2005

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Publisher
Emerald Publishing
Copyright
Copyright © 2005 Emerald Group Publishing Limited. All rights reserved.
ISSN
1468-4527
DOI
10.1108/14684520510607560
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to classify the most important metrics proposed for web information systems, with the aim of offering the user a global vision of the state of the research within this area. Design/methodology/approach – WQM distinguishes three dimensions related to web features, lifecycle processes and quality characteristics. A range of recently published (1992‐2004) works that include web metrics definitions have been studied and classified within this model. Findings – In this work, a global vision of web metrics is provided. Concretely, it was found that about 44 percent of metrics are related to “presentation” and that most metrics (48 percent) are usability metrics. Regarding the life cycle, the majority of metrics are related to operation and maintenance processes. Nevertheless, focusing on metrics validation, it was found that there is not too much work done, with only 3 percent of metrics validated theoretically and 37 percent of metrics validated empirically. Practical implications – The classification presented tries to facilitate the use and application of web metrics for different kinds of stakeholders (developers, maintainers, etc.) as well as to clarify where web metric definition efforts are centred, and thus where it is necessary to focus future works. Originality/value – This work tries to cover a deficiency in the web metrics field, where many proposals have been stated but without any kind of rigour and order. Consequently, the application of the proposed metrics is difficult and risky, and it is dangerous to base decisions on their values.

Journal

Online Information ReviewEmerald Publishing

Published: Jun 1, 2005

Keywords: Worldwide web; Quality; Measurement

References

  • Where now for development methodologies?
    Avison, D.E.; Fitzgerald, G.
  • Estimating the design effort of web applications
    Baresi, L.; Morasca, S.; Paolini, P.
  • Structural analysis of hypertexts: identifying hierarchies and useful metrics
    Botafogo, R.; Rivlin, E.; Schneiderman, B.
  • A survey of web metrics
    Dhyani, D.; Ng, W.K.; Bhowmick, S.S.
  • Tools and approaches for developing data‐intensive web applications: a survey
    Fraternali, P.
  • Hyperlink analysis for the web
    Henzinger, M.
  • The state‐of‐the‐art in automating usability evaluation of user interfaces
    Ivory, M.Y.; Hearst, M.
  • Empirically validated web page design metrics
    Ivory, M.Y.; Sinha, R.R.; Hearst, M.A.
  • Navigating in hyperspace: designing a structure‐based toolbox
    Rivlin, E.; Botafago, R.; Schneiderman, B.

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