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The field of website quality evaluation attracts the interest of a range of disciplines, each bringing its own particular perspective to bear. This study aims to identify the main characteristics – methods, techniques and tools – of the instruments of evaluation described in this literature, with a specific concern for the factors analysed, and based on these, a multipurpose model is proposed for the development of new comprehensive instruments.

Following a systematic bibliographic review, 305 publications on website quality are examined, the field's leading authors, their disciplines of origin and the sectors to which the websites being assessed belong are identified, and the methods they employ characterised.

Evaluations of website quality tend to be conducted with one of three primary focuses: strategic, functional or experiential. The technique of expert analysis predominates over user studies and most of the instruments examined classify the characteristics to be evaluated – for example, usability and content – into factors that operate at different levels, albeit that there is little agreement on the names used in referring to them.

Based on the factors detected in the 50 most cited works, a model is developed that classifies these factors into 13 dimensions and more than 120 general parameters. The resulting model provides a comprehensive evaluation framework and constitutes an initial step towards a shared conceptualization of the discipline of website quality.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.

This paper aims to propose a conceptual model to examine the effect of an augmented reality (AR)–based product display (vs a picture-based product display) on interactivity, vividness, website quality and consumer responses. In addition, the moderating role of the need for touch (NFT) in the effect of AR on media features is identified.

Hypotheses are tested using a one-factor between-subjects design for both a student sample (Study 1, N = 120) and a nonstudent sample (Study 2, N = 272). Data are analyzed using a series of analyses of variance, multivariate analyses of covariance and structural equation modeling.

Study 1 shows that an AR-based product display generates greater website quality, interactivity and vividness than a picture-based product display. Moreover, an AR-based product display improves interactivity and vividness only for high-NFT consumers; however, no significant difference emerged for low-NFT consumers. Study 2 replicates and extends our findings by identifying the specific processes that consumers go through when evaluating a website.

The current research advances the understanding of how product presentation technologies can attract customers with different haptic orientations and provides practical implications for online retailers interested in improving their customers' e-commerce experience.

Consumer-perceived review attitude determines consumer overall information adoption and is a core part of consumer’s online-shopping. This study aims to focus on factors that could influence consumer review attitude and can be used by marketers to shape individual information perception.

The study used the questionnaire method to collect data from online shoppers and the modelling of structural equations as an empirical approach to analyse the data.

The findings demonstrate that both systematic and heuristic cues impact the reviewer’s credibility and perceived website attitude differently, which, in turn, influence review attitude. Review characteristics, such as factuality, consistency and relevancy, have a positive relationship with reviewer credibility, while only review consistency and relevancy appears to have a relationship with review attitude. Website characteristics such as reputation, familiarity and social interactivity positively influence the website attitude, which positively influences review attitude. Apart from this, review skepticism has a significant negative relationship with review attitude.

This study could help to foster a positive attitude towards online reviews. Digital marketers need to motivate trusted reviewers to post consistent, fact-based reviews. Further improving the overall website reputation and interactivity could bring a positive attitude towards the reviews. Also, digital marketers must filter and avoid contradictory reviews or reviews that have a bipolar message and reviews expressing numerous emotions to enhance review relevance and consistency.

The current study addresses the need to understand the formation of consumer review attitude through both review and website characteristics using heuristic – systematic model. The paper captures the complex process undergone by the consumer to decipher review attitude and thereby extend the understanding of consumer information processing.

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

Do luxury consumers negatively evaluate digital interactions (website and social media) by international luxury brands? The topic has received much debate. The authors argue that luxury brand personality (modern vs. traditional), which encompasses a more stable form of brand identity in global markets, affects evaluations of digital interactions. They further investigate the role of self-brand connection in this process.

Three experiments on Prolific use a European sample and manipulate a single factor between subjects (modernity: less vs. more; traditionality: less vs. more) of French luxury brands and measure evaluations as the dependent variable. Two studies assesses self-brand connection (continuous) as a moderator (studies 2a, 2b). Study 2b rules out some alternative explanations, with culture (independent vs. collectivist) as an independent variable. A fourth study, using a North American sample on CloudResearch, assesses the effect of personality manipulation (more modernity vs. more traditionality) on consumer evaluations of an Italian brand, and assesses ubiquity perceptions as a mediator.

Consumers evaluate digital interactions of international luxury brands less favorably when luxury brand personality exhibits more (vs. less) modernity or less (vs. more) traditionality. Perceptions of ubiquity mediate these relationships. When self-brand connection is high, this effect is attenuated.

The research sheds light on the debate on whether luxury brands should create digital interactions in international markets, given that these global brands operate in multiple channels. Findings show that luxury brands can develop strategies based on aspects of their brand identity, a less malleable feature of brand identity within global markets. Additionally, the research contributes to the conversation about a global luxury market. In short, the findings offer evidence in favor of brand identity (personality) influencing the digital channel strategy a brand should undertake in international markets, first, followed by consumer needs.

This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).

This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.

The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.

This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.

This empirical study uses the stimulus-organism-response (S-O-R) framework to examine the interrelationships amongst hotel websites and app quality, flow, telepresence, user engagement and booking intentions.

Data from two different datasets, including users of hotel websites (N sample 1 = 257) and hotel mobile apps (N sample 2 = 292), were collected. Partial least squares (PLS-SEM) was used to test the research model.

Findings indicate that the quality of the hotel websites and mobile apps positively influences telepresence, flow and engagement. Telepresence and flow positively affect the users booking intentions for both the samples. However, for hotel website users, engagement has a no-significant effect on booking intentions. Finally, telepresence has a non-significant effect on flow, and flow has a non-significant effect on engagement for both the users of hotel websites and mobile apps.

This study uses two datasets to understand how hotel booking channel (hotel website and mobile app) quality leads to booking intentions by tapping into telepresence, flow and engagement.

While known by many names, qualifying exams function as gatekeepers to graduate student advancement to PhD candidacy, yet there has been little formal study on best qualifying exam practices particularly in biomedical and related STEM PhD programs. The purpose of this study is to examine the current state of qualifying exams through an examination of the literature and exploration of university-wide policies.

The authors conducted a literature review of studies on qualifying exams and completed an external evaluation of peer institutions’ and internal institutional qualifying exam requirements to inform our discussion of qualifying exams practices in PhD training at a research-intensive US institutions.

This study identified the need for more research on qualifying exams to establish evidence-based best practices. The authors found a wide variety of qualifying exam formats, with little evidence in support for specific formats. The authors also found little evidence that student expectations are made clear. The lack of evidence-based best practices coupled with insufficient clarity for students has a real potential to disadvantage PhD students, particularly first generation, underrepresented minority, international and/or other trainees who are not privileged or socialized to navigate training environments with vague landmarks such as the qualifying exams.

There are very few studies that evaluate qualifying exams in US doctoral education, particularly in STEM fields, and to the authors’ knowledge, there has been no analysis of campus-wide policies on qualifying exams reported. The lack of evidence for best practices and the need for to evaluate the implementation and effectiveness of qualifying exams are discussed.

Color psychology theory reveals that complex images with very varied palettes and many different colors are likely to be considered unattractive by individuals. Notwithstanding, web content containing social signals may be more attractive via the initiation of a social connection. This research investigates a predictive model blending variables from these theoretical perspectives to determine crowdfunding success.

The research is based on data from 176,614 Kickstarter projects. A number of machine learning and artificial intelligence techniques were employed to analyze the listing images for color complexity and the presence of people, while specific language features, including socialness, were measured in the listing text. Logistic regression was applied, controlling for several additional variables and predictive model was developed.

The findings supported the color complexity and socialness effects on crowdfunding success. The model achieves notable predictive value explaining 56.4% of variance. Listing images containing fewer colors and that have more similar colors are more likely to be crowdfunded successfully. Listings that convey greater socialness have a greater likelihood of being funded.

This investigation contributes a unique understanding of the effect of features of both socialness and color complexity on the success of crowdfunding ventures. A second contribution comes from the process and methods employed in the study, which provides a clear blueprint for the processing of large-scale analysis of soft information (images and text) in order to use them as variables in the scientific testing of theory.