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The purpose of the present work was to design a comprehensive weighted features model for the specific evaluation of archival websites, and to apply it in practice to the particular population of Spain's web archives, ranking them in terms of quality based on the features they include.

The design of the weighted features model is based on two parameters: the weight assigned to each feature according to its relevance for information retrieval from archival websites, and the archival website's degree of compliance with that feature.

The results of the practical application of the model to the case of Spanish web archives showed that, contrary to prior expectation, factors which are intrinsic to the geographical region of Spain that the archive belongs to, such as economic level or degree of commitment to specific archival legislation, do not directly influence its website's quality ranking. Instead, the authors conclude that the population of archival websites presents its own particular behaviour.

There has been a general lack of research specific to the analysis of the features of archival websites. The present work represents a certain advance in this regard in its proposal of a comprehensive weighted model of indicators for the specific evaluation of archival websites.

This paper proposes a framework that automatically assesses content coverage and information quality of health websites for end-users.

The study investigates the impact of textual and content-based features in predicting the quality of health-related texts. Content-based features were acquired using an evidence-based practice guideline in diabetes. A set of textual features inspired by professional health literacy guidelines and the features commonly used for assessing information quality in other domains were also used. In this study, 60 websites about type 2 diabetes were methodically selected for inclusion. Two general practitioners used DISCERN to assess each website in terms of its content coverage and quality.

The proposed framework outputs were compared with the experts' evaluation scores. The best accuracy was obtained as 88 and 92% with textual features and content-based features for coverage assessment respectively. When both types of features were used, the proposed framework achieved 90% accuracy. For information quality assessment, the content-based features resulted in a higher accuracy of 92% against 88% obtained using the textual features.

The experiments were conducted for websites about type 2 diabetes. As the whole process is costly and requires extensive expert human labelling, the study was carried out in a single domain. However, the methodology is generalizable to other health domains for which evidence-based practice guidelines are available.

Finding high-quality online health information is becoming increasingly difficult due to the high volume of information generated by non-experts in the area. The search engines fail to rank objective health websites higher within the search results. The proposed framework can aid search engine and information platform developers to implement better retrieval techniques, in turn, facilitating end-users' access to high-quality health information.

Erroneous, biased or partial health information is a serious problem for end-users who need access to objective information on their health problems. Such information may cause patients to stop their treatments provided by professionals. It might also have adverse financial implications by causing unnecessary expenditures on ineffective treatments. The ability to access high-quality health information has a positive effect on the health of both individuals and the whole society.

The paper demonstrates that automatic assessment of health websites is a domain-specific problem, which cannot be addressed with the general information quality assessment methodologies in the literature. Content coverage of health websites has also been studied in the health domain for the first time in the literature.

This paper aims to identify the reasons for the lower ranking of the Online Service Index of Sri Lanka under the United Nations E-Government Readiness Index. The study is conducted as a comparative study on selected Asian countries and suggests remedial measures for the improvement of the status of e-government of Sri Lanka.

In this regard, as the sample of websites ranked according to the Online Service Index of the United Nations, five government websites of Sri Lanka, India, Bangladesh and Singapore were selected. They are the national portal and the websites of the five Ministries: The Ministry of Education, Finance, Health, Labor and of Social Services. Asian countries selected are India, Bangladesh and Singapore including Sri Lanka. Observation method was the mainly used method for data collection. The websites were evaluated in contrast with the help of the “Main features reviewed by the United Nations E-government Survey” as the checklist. Substantial description and scoring methods were used for the analysis of the data and the presentation of the findings of the study.

Thus, several weaknesses of the online services of the government websites of Sri Lanka were identified. Among them, the major reasons identified for the lower rank of the Sri Lankan Online Service Index were, for example, the inability to identify the exact website of national portal, the lack of accessibility or usability features, the weaknesses in the active maintenance of the “Contact us” feature, service-delivery capability features, citizen participation and also interconnectedness features. The above weaknesses have been the key/root causes for the decline of the rank of the Online Service Index of Sri Lanka.

From five government websites, selected three foreign Asian countries were in focus because of practical limitations. Another difficulty faced in the analysis and comparison of the websites was that the information with regard to the United Nations evaluation methodology/criteria has not been adequately provided.

The findings of this study provide information for the policy makers, web standards, evaluation criteria developers and almost all the government organizations to address key issues related to this field for the maximization of citizen participation, the enhancement of the service-delivery capabilities and accessibility features of websites to improve the online services of the government. This study unfolded several areas for the future researchers. Those researches can also be conducted based on sub indexes of the United Nations E-Government Readiness Index. The same method could be used to examine Human Capital Index, Telecommunication and Infrastructure Index and Citizen Participation Index. This research could also be expanded through observations of foreign countries.

This paper provides an overview of the quality of government websites of Sri Lanka compared to the selected Asian countries. Through the utilization of this scoring method, four major weaknesses that contribute to the lower ranking of the online service of Sri Lanka were identified with suggestions indented for the improvement of the government websites.

Phishing attacks have evolved in recent years due to high-tech-enabled economic growth worldwide. The rise in all types of fraud loss in 2019 has been attributed to the increase in deception scams and impersonation, as well as to sophisticated online attacks such as phishing. The global impact of phishing attacks will continue to intensify, and thus, a more efficient phishing detection method is required to protect online user activities. To address this need, this study focussed on the design and development of a deep learning-based phishing detection solution that leveraged the universal resource locator and website content such as images, text and frames.

Deep learning techniques are efficient for natural language and image classification. In this study, the convolutional neural network (CNN) and the long short-term memory (LSTM) algorithm were used to build a hybrid classification model named the intelligent phishing detection system (IPDS). To build the proposed model, the CNN and LSTM classifier were trained by using 1m universal resource locators and over 10,000 images. Then, the sensitivity of the proposed model was determined by considering various factors such as the type of feature, number of misclassifications and split issues.

An extensive experimental analysis was conducted to evaluate and compare the effectiveness of the IPDS in detecting phishing web pages and phishing attacks when applied to large data sets. The results showed that the model achieved an accuracy rate of 93.28% and an average detection time of 25 s.

The hybrid approach using deep learning algorithm of both the CNN and LSTM methods was used in this research work. On the one hand, the combination of both CNN and LSTM was used to resolve the problem of a large data set and higher classifier prediction performance. Hence, combining the two methods leads to a better result with less training time for LSTM and CNN architecture, while using the image, frame and text features as a hybrid for our model detection. The hybrid features and IPDS classifier for phishing detection were the novelty of this study to the best of the authors' knowledge.

Despite promising conceptual developments in value co-creation behaviors, the scholarly attention afforded to the importance of the university website features in strengthening the university brand image and reputation through students’ value co-creation behaviors is limited. University website features are conceptualized as a hierarchical construct with three dimensions: usability, availability and information. This study aims to investigate the effect of university website features and value co-creation behaviors of students on promoting brand image and brand reputation at Islamic Azad University in Iran.

This study is quantitative. Using convenience sampling techniques, a responsive group of 384 students was chosen from the Islamic Azad University of Tehran in Iran. Survey methods were used for data collection. Partial least squares structural equation modeling was used to test the derived hypotheses.

The findings of this study indicated that website features have a positive effect on fostering value co-creation behaviors (participation and citizenship behavior), and participation behavior, in turn, improves university brand image and reputation. At the same time, among value co-creation behaviors, citizenship behavior has no impact on the university’s brand image. Finally, the brand image formed through website features and participation behavior positively affects brand reputation.

This study was conducted in the higher education (HE) sector in one cosmopolitan Iranian city (i.e. Tehran), to which Iranians from other cities travel for studying. Thus, the results of this survey include a variety of subcultures. In the future, a study that incorporates all major metropolitan cities of Iran may increase the generalizability of the findings. Unrelated to the purpose of this study, a future research study may extend the currently studied geographical dimensions and examine the antecedents of university brand reputation across different nations using a cross-cultural approach.

Pragmatically, the findings of this study urge university policymakers, information technology managers and marketers to consider the university website’s unique role in assisting co-creation behavior, which in turn promotes university brand image and reputation in the HE market. One of the ways to assess a university’s brand image and reputation is through the university ranking system. Ascending the ranking system can allow a university to attract qualified students.

These findings contribute to the marketing literature by empirically validating the three elements in the website features construct, providing intelligence on how website features can drive value co-creation behaviors, brand image and reputation. Also, results revealed that the brand image of universities positively affects brand reputation. This study highlights the importance of national and international rankings of universities and students’ sensitivity to such rankings. Undoubtedly, this is evident in Iranian students’ behavior in selecting their university.

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately.

Hyperlink indicators along with URL-based features are used to build the identification model. In the proposed approach, very simple rules are first extracted based on individual features to provide meaningful and easy-to-understand rules. Then, the F-measure score is used to select high-quality rules for identifying phishing websites. To construct a reliable and promising phishing website identification model, the selected rules are integrated using a simple neural network model.

Experiments conducted using self-collected and benchmark data sets show that the proposed approach outperforms 16 commonly used classifiers (including seven non–rule-based and four rule-based classifiers as well as five deep learning models) in terms of interpretability and identification performance.

Investigating patterns of phishing websites based on hyperlink indicators using the efficient rule-based approach is innovative. It is not only helpful for identifying phishing websites, but also beneficial for extracting simple and understandable rules.

This study aims to better understand the communication of sustainability by Canadian universities, specifically the use of websites, interactive features and sustainability plans.

A total of 95 Canadian universities were included in this study. The mixed-methods approach sought to capture the communication of sustainability via websites, the interactive features used, as well as to evaluate the quality of sustainability plans.

The study revealed that 67% of universities address sustainability on their websites. On average, universities offer three to four interactive features on their sustainability-related Web pages, and the average score of the quality of campus sustainability plans was 29 (out of 41).

This study does not investigate the extent to which interactive features enhance the involvement and participation in sustainability efforts or the extent to which the sustainability plans were put into practice by universities.

The findings assist with understanding how higher education institutions (HEIs) can enhance their sustainability communication via their websites to encourage interaction and engagement in campus sustainability. The findings can also help universities to enhance the effectiveness of sustainability plans.

To the best of the authors’ knowledge, this is the first research to assess sustainability content and the interactive features on sustainability-related pages of Canadian universities’ websites. The quality of sustainability plans is also evaluated. The study informs the present understanding of communicating sustainability by Canadian universities and provides a basis for future investigations in HEIs in Canada and beyond.

Purpose – The purpose of this research is to analyse the display of digital images found on clothing and textile collection websites. Design/methodology/approach – Features noted included where on the website the images were found, such as in a display or as part of a database. Display features are documented, including enlargement abilities, the view of the artefact, the use of dress forms and mannequins, and the context in which the artefact was pictured. The text that describes the artefact is also documented. The instrument was a content analysis of clothing and textile collection websites. Data were collected in 2006 from 57 clothing and textile collection websites. Findings – All 57 costume and textile museums had images of collection artefacts online, with the majority sharing a featured artefact. Almost half of the websites used images in databases and displays. Enlargement abilities were not common; most of the visuals showed the front view of the artefact. Enlargements were more common in displays. Mannequins and dress forms were used infrequently. Detailed text to explain the artefacts was available in the databases. Research limitations/implications – The research was limited to observing 57 websites. Originality/value – Common features used by costume and textile museums when displaying collection pieces online were identified. Suggestions as to what content to include in a website for clothing and textile collections are discussed in light of the data collected.

To examine the relationships among website design features, consumer experience responses and patronage intention toward online mass customization (OMC) apparel websites.

A total of 312 useable online surveys were obtained from Mainland China consumers. Multi-item scales were adopted to measure eight constructs: visual design; information quality; entertainment, aesthetic, educational, escapist experiences; flow; and patronage intention. Structural equation modeling (SEM) was conducted to determine factor structures and to test the hypothesized relationships among website design features, 4Es (entertainment, aesthetic, educational and escapist experiences), flow and consequent purchase intention toward OMC apparel websites.

All hypotheses, but one, were supported. OMC website visual design; information quality; and entertainment, aesthetic and educational experiences had a positive effect on consumer patronage intention.

Limitations include using a sample of consumers from major cities in China; results cannot be generalized to all Chinese consumers. Websites were not actively navigated. Additionally, the present study examined only two dimensions of OMC website quality, visual design and information quality; more tangible and specific features could be considered in future research.

The findings provide website designers and marketers with insights into experiences that may lead to an increase in patronage intention toward OMC websites.

The study provides evidence that flow helps explain the impact of experiential value (i.e. 4Es) from website design features on patronage intention.

Using asymmetric impact–performance analysis for examining an asymmetric relationship between user satisfaction and website features, the present research aims to identify features of high priority for quality improvement. For doing so, the current research was conducted in the context of the E-learning website of the most prestigious university in Iran, namely, the University of Tehran.

The main question was which of the three groups of basic, performance and excitement factors has the required dimensions of the quality of the website based on the model WebQual 4.0 by considering Kano’s user satisfaction model and impact–performance analysis. This is a descriptive survey, applied and cross-sectional study. The study population included Tehran University’s students who enrolled in virtual courses in the academic year 2020–2021 from which a sample of 457 students was selected. The data collection tool was the questionnaire of Webqual 4.0, as well as a researcher-made questionnaire to measure end-user satisfaction.

Using structural equation modeling and multiple regression, the findings showed that the customer’s overall satisfaction with the mentioned website is primarily affected by the feature interaction with services, including the two structures of trust and empathy, and then the dimensions of usability and quality of information. Examining the Webqual 0.4 dimensions indicated that the website usability dimension is a part of the high-performance excitement factors group, the information quality dimension is a part of the high-performance basic factors group and the website interaction dimension is in the low-performance basic factors group.

The research is highly innovative taking the theoretical model of Kano and methodological investigation of asymmetric impact–performance analysis into consideration alongside the WebQual 4.0 as a fundamental model for website assessment. Moreover, the research was conducted on an E-learning website, which is unique and a necessity amid the COVID-19 pandemic.