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The current study aims to empirically analyze the influence of different information sources, together with the persuasiveness of recommender systems (RSs) on the consumer’s purchase intention (PI). It also expands the research on RSs from the point of view of consumer behavior and psychology, considering perceived usefulness and relevance. In addition, it analyzes how different types of personalized recommendations, along with non-personalized ones, influence PI.

The proposed model has been validated using partial least squares structural equation modeling (PLS-SEM), based on the data collected from 597 online shoppers.

This study proves that both information search and RSs influence PI, being complementary rather than mutually exclusive. Recommender systems’ findings indicate that the PI is primarily influenced by the perceived relevance of RSs, the information provided by manufacturers and reviews. Moreover, only the influence of the perceived usefulness of personalized recommendations strongly affects PI. Conversely, non-personalized recommendations do not affect PI.

Developers should focus on increasing the perceived usefulness and relevance of RSs. Thus, they could adopt the hybridization of RSs with the aggregation of both personal shopping behavior and social network contacts. It should integrate information signals from multiple sources to include sentiment extracted from reviews or links to the manufacturer’s page. Furthermore, the recommendation of discounted products must be only for products preferred by customers, because only these influence the PI.

This research provides a structural model that examines together, for the first time, the influence on the PI of the main RSs and sources of information.

This paper aims to develop an efficient algorithm combining straightforward response surface functions with Monte Carlo simulation to conduct seismic reliability analysis in a systematical way.

The representative slip surfaces are identified and based on to calibrate multiple response surface functions with acceptable accuracy. The calibrated response surfaces are used to determine the yield acceleration in Newmark sliding displacement analysis. Then, the displacement-based limit state function is adopted to conduct seismic reliability analysis.

The calibrated response surface functions have fairly good accuracy in predicting the yield acceleration in Newmark sliding displacement analysis. The seismic reliability is influenced by such factors as PGA, spatial variability and threshold value. The proposed methodology serves as an effective tool for geotechnical practitioners.

The multiple sources of a seismic slope response can be effectively determined using the multiple response surface functions, which are easily implemented within geotechnical engineering.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

This article explores the synergy between journalism studies and computer science in the context of observing online news. By establishing web applications of online media observatories as research tools, researchers can employ various analytical approaches to gain valuable insights into online news discourse and production.

Drawing eight months of data (01.08.2022–30.04.2023) from the Labservatory’s web application, i.e. over 250,000 news items, the article demonstrates how some of this web application’s main functionalities may be useful in implementing (1) news flow analysis, (2) news topic distribution analysis and (3) media discourse analysis.

The capabilities provided by this web application, (1) to simultaneously analyse the daily news production of ten media outlets with varying features, (2) to rapidly collect a large volume of news items, (3) to identify the news categories as classified by the media themselves, (4) to present the results of the search in relevance order and (5) to automatically generate a search report, highlight the significance of this interdisciplinary collaboration for implementing comprehensive analyses of online news.

The article concludes by emphasising the importance of continuing this joint effort, as it opens new avenues for further research and provides a deeper grasp of the intricate relationship between journalism, technology and society in the digital era. The Labservatory also contributes to society since it may be used by the broader public for immediate access to more pluralistic information and thus for promoting both news media literacy and news media accountability.

Access to patent-related information is facilitated in large part by repositories of patents. Additionally, patent repositories support transparency and knowledge exchange, both of which can spark new alliances and collaborations. In addition to serving as a source of inspiration for future inventions, they allow companies, researchers and inventors to look up current patents and prevent infringement. Globally, the scientific and academic communities are becoming increasingly interested in open-access repositories. Countries throughout the world have kept up their repositories because of their significance. A directory of open access repositories (OpenDOAR) is a reliable source with minimally inaccurate or dubious content, having been meticulously chosen and validated. It acts as a global registration hub, enabling the visibility and accessibility of research contributions. Hence, this study aims to look into the current status of open-access repositories for archiving “Patents”, at the global level in OpenDOAR by analysing the different characteristic features of repositories.

The advanced search strategy of the directory of open-access repositories (www.opendoar.org/) is used to extract the data. The data extraction process was carried out on 28th March 2023. The study limited its search to “Patents” only, among the different content types listed in it. A total of 253 repositories were retrieved that contained the selected content type. However, the advanced search feature was combined one by one with other available parameters to retrieve the data. The gathered data was saved in MS Excel for further analysis. Moreover, the open access policies, open archives initiative protocol for metadata harvesting (OAI-PMH) and language interface of repositories were manually looked up from each repository/record information. To present the findings, charts and tables were used to visualize the gathered data effectively.

The study shows that repositories have increased over the years, with the highest number established in 2022. The UK has emerged as the most prominent country contributing to the development of repositories for archiving patents. The majority of the repositories are institutional, and DSpace is the most commonly used software for their creation. While Web 2.0 tools are not widely used, however, a significant number of repositories have incorporated RSS feeds, Atom and social media. Open access policies play a vital role in managing the content archived in the repositories, and only a small percentage of the repositories were found to be following them. However, the majority of the repositories have shown OAI-PMH compliance. English is the most commonly preferred interface language by repositories for archiving patents. These findings suggest that there is still significant room for improvement in the development and management of repositories, and adherence to open-access policies could play a crucial role in ensuring their sustainability and usefulness in the future.

To the best of the author’s knowledge, the study is the first of its type that examines the global landscape of open-access patent repositories.

This study aims to highlight the many distinguishing characteristics of open-access repositories that archive “Patents” in the Directory of Open-Access Repositories (OpenDOAR) provided by Asian nations.

The OpenDOAR was chosen as a data collection tool that provides a quality-assured list of repositories indexed globally. The data was extracted on 28 March 2023.

The study found that only eight Asian countries contributed to open-access repositories on OpenDOAR, with China being the highest contributor. These countries mainly focused on institutional repositories, primarily using DSpace and English as the main language interface. Web 2.0 tools, especially RSS and Atom, were commonly used, along with some presence of social media platforms on the sites, although to a lesser extent. While many repositories followed the OAI-PMH protocol, a considerable portion did not adopt open-access policies.

To the best of the authors’ knowledge, this study is the first one that brings to light the different features of repositories archiving one of the important content types, i.e. “Patents” in the OpenDOAR by Asian countries.

Social media marketing (SMM) denotes attaining website traffic or attention through social media platforms. The paper aims to focus on examining the viewpoint of library professionals from different universities along with the user respondents from different disciplines and universities on the role of social media tools to market university libraries.

It is a survey-based study that used the questionnaire as its chief data collection instrument designed to be administered to library professionals (n = 100) and users (n = 1,189) from eight universities. The study also adopted the general observation and interview methods to supplement the data. The data was analyzed using SPSS software, and Chi-square test and ANOVA were applied to ascertain the significant variations in viewpoints of the library professionals and the users.

The research study showed that library professionals (from different universities) and users (from different disciplines and universities) felt that social media could be an appropriate marketing tool for libraries in the future. Observations during data collection highlighted a lack of confidence and unwillingness among library professionals to implement any changes in the present time.

The present study provides some significant insights for improving the current situation of the libraries under study in terms of increasing awareness among the students and adopt social media tools for marketing of library facilities and services in future. It is important to note that a few issues that came into light during data collection were a marked lack of willingness and prevalence of less confidence among the library professionals to execute or implement the social media tools to market library resources and services among the users.

SMM programs focus on creating content that attracts attention and encourages readers to use it. This study attempts to fill the gap in of marketing in libraries through social media. The paper offers insights into the use of marketing tools for promoting library resources and services as per the needs of library users. The research work differs from other studies undertaken on library marketing related to social media as it has included both library professionals and users together to obtain a better picture in this regard.

This paper aims to examine accessibility in the built environment and tries to determine the physical and attitudinal barriers affecting Persons with Visual Disabilities' (PWVDs) experience on the University of Jordan (UJ) campus.

This is a descriptive mixed-methods study, based on the following: data collection regarding PWVDs' services at UJ; semi-structured interviews with PWVDs and with some employees at UJ; observations, photographs and direct measurements during campus tours; accompanying one student with poor eyesight when navigating through UJ campus; then, analyzing data in light of the national code's accessibility checklist.

UJ campus suffers from many shortcomings regarding accessibility; these include an insufficient pedestrian environment, limited tactile paths, low illuminance levels in lecture halls and other inadequate services. Besides, there are many infringements on PWVDs' paths, due to either new expansions or unconscious behavior. Moreover, interpersonal barriers prevent PWVDs from using assistive equipment and accommodation. The study concludes that preserving pedestrians' rights, monitoring new expansions, renovating the UJ campus in accordance with national codes and international standards, improving PWVDs services and awareness-raising programs are needed to ensure accessibility for PWVDs.

New legislation has been recently passed regarding accessibility in Jordan, and – on the UJ campus – the first phase of tactile paving has been installed. This paper is believed to be the first of its kind to evaluate PWVDs' services following the new changes. The study's methodology might also be deemed useful to stakeholders when enabling the built environment.

This study aims to identify the main challenges to achieving humanitarian logistics in the context of United Nations peace missions in sub-Saharan Africa and to present suggestions for overcoming the logistical gaps encountered.

The methodological approach of the work focuses on the comparative case study of the United Nations Mission in South Sudan, the United Nations Multidimensional Integrated Stabilisation Mission in the Central African Republic and The United Nations Organisation Stabilisation Mission in the Democratic Republic of Congo from 2014 to 2021. The approach combined a systematic literature review with the authors’ empirical experience as participant observers in each mission, combining theory and practice.

As a result, six common challenges were identified for carrying out humanitarian logistics in the three peace missions. Each challenge revealed a logistical gap for which an appropriate solution was suggested based on the best practices found in the case study of each mission.

This paper presents limitations when addressing the logistical analysis based on only three countries under the UN mission as a case study, as well as conceiving that certain flaws in the system, in the observed period, are already in the process of correction with the adoption of the 2016–2021 strategy by the UN Global Logistic Cluster. The authors suggest that further studies can be carried out by expanding the number of cases or using countries where other bodies (AU, NATO or EU) work.

To the best of the authors’ knowledge, this study is the first comparative case study of humanitarian logistics on the three principal missions of the UN conducted by academics and practitioners.