What is it about?

Privacy issues are a top priority in web design. However, websites’ evaluation methods do not consider legal and ethical issues. This article proposes a fuzzy logic–based methodology for evaluating websites’ compliance with legal and ethical principles. Using fuzzy Delphi and fuzzy numbers, the methodology develops the Fuzzy Legal and Ethical Compliance Index (FLECI) that addresses the inherited vagueness of the evaluation process and calculates websites’ conformity to legal and ethical guidelines. To illustrate the proposed methodology, this research collects data and then evaluates and classifies 100 websites with respect to their privacy policies using fuzzy equivalence. This article provides a foundation for the development of comprehensive website evaluation methods that include privacy and ethical issues in their evaluations. Future research can investigate the applicability of the proposed methodology and the fuzzy numbers calculated in this article in websites across industries and cultural activities.

Featured Image

Why is it important?

This paper addresses the need to evaluate websites based on their degree of compliance to “Legal and Ethical Website Guidelines” regarding the collection, storage and use of personal information. In this context, the FLEWE, which is a fuzzy logic based evaluation methodology that can be used either during the design of a website or its evaluation, is proposed. Fuzzy logic addresses the inherited vagueness and imprecision of the evaluation procedure compared with the conventional “crisp” evaluation approaches that are not always suitable. The methodology aggregates experts’ opinions to assess the compliance of a website. Within the context of the proposed FLEWE methodology the FLECI index is developed and used to calculate the relative importance of the evaluation criteria and subcriteria in fuzzy numbers. These importance weights can be used to design and evaluate websites. This methodology applied fuzzy classification with an equivalence relation as an appropriate technique that can be used to classify websites into corresponding classes. To examine the applicability of the proposed methodology, a list of 100 diversified websites with high Internet traffic was used. The results indicate that the proposed methodology provides the conceptual framework and tools to measure websites’ compliance to “Legal and Ethical Website Guidelines”. It enables the methodology to adapt to legislation changes by altering the criteria in the FLECI or their corresponding weights. The classification of websites based on their compliance scores can be used as a tool to identify websites’ deficiencies with respect to legal and ethical guidelines and assist practitioners in managing their improvement action plans. It is also useful for website users and customers learn how carefully and elaborately website management considers legal and ethical issues. By analysing 100 sample websites, this study identifies differences that are reflected in four classes of websites that represent different levels of legal and ethical compliance. Each class indicates what is done and what needs to be done for each website. Future studies can investigate the applicability of the methodology proposed in this paper in websites across industries, cultures and areas of social activities and businesses profile pattern that may reflect and explain the differences with respect to the degree of the compliance to LEWG. The proposed fuzzy methodology is potentially useful to both researchers and practitioners who perform evaluation studies, where vagueness or imprecision exist. The methodology can be used to evaluate and record websites’ compliance to “Legal and Ethical Website Guidelines” over a period of time.

Read the Original

This page is a summary of: Evaluation of websites’ compliance to legal and ethical guidelines: A fuzzy logic–based methodology, Journal of Information Science, March 2017, SAGE Publications,
DOI: 10.1177/0165551517697610.
You can read the full text:

Read

Contributors

The following have contributed to this page