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In community question answering (CQA), people who answer questions assume readers have mastered the content in the answers. Nevertheless, some readers cannot understand all content. Thus, there is a need for further explanation of the concepts that appear in the answers. Moreover, the large number of question and answer (Q&A) documents make manual retrieval difficult. This paper aims to alleviate these issues for CQA websites.

In the paper, an algorithm for recommending explanatory Q&A documents is proposed. Q&A documents are modeled with the biterm topic model (BTM) (Yan et al., 2013). Then, the growing neural gas (GNG) algorithm (Fritzke, 1995) is used to cluster Q&A documents. To train multiple classifiers, three features are extracted from the Q&A categories. Thereafter, an ensemble classification model is constructed to identify the explanatory relationships. Finally, the explanatory Q&A documents are recommended.

The GNG algorithm shows good clustering performance. The ensemble classification model performs better than other classifiers. The both effect and quality scores of explanatory Q&A recommendations are high. These scores indicate the practicality and good performance of the proposed recommendation algorithm.

The proposed algorithm alleviates information overload in CQA from the new perspective of recommending explanatory knowledge. It provides new insight into research on recommendations in CQA. Moreover, in practice, CQA websites can use it to help retrieve Q&A documents and facilitate understanding of their contents. However, the algorithm is for the general recommendation of Q&A documents which does not consider individual personalized characteristics. In future work, personalized recommendations will be evaluated.

A novel explanatory Q&A recommendation algorithm is proposed for CQA to alleviate the burden of manual retrieval and Q&A overload. The novel GNG clustering algorithm and ensemble classification model provide a more accurate way to identify explanatory Q&A documents. The method of ranking the explanatory Q&A documents improves the effectiveness and quality of the recommendation. The proposed algorithm improves the accuracy and efficiency of retrieving explanatory Q&A documents. It assists users in grasping answers easily.

This study is based on the extended theory of planned behavior (TPB) and attempts to shed light on what influences restaurant consumers’ intentions to eat locally sourced meals.

Data from 698 respondents were gathered through a web-based survey employing a quantitative methodology.

The findings indicated that several motivating factors, subjective norms and perceived behavioral control positively influence respondents’ attitudes toward dining at restaurants serving meals that are obtained locally. Also, attitudes significantly predicted intentions and mediated the relationship between the motivating factors and intention to consume local meals. Furthermore, subjective norms and perceived behavioral control moderated the relationship between attitude and intention.

The study offers implications for both theory and practice. In the context of Egypt in particular, this study advocates for sustainable food production and consumption in restaurants. The study focused only on consumers; it suggests that subsequent research should examine the restaurant operators’ perspective.

To draw in and please more locavores, restaurant management can use buzzwords like “safe food,” “fresh food” and “environmental labels.” They should also provide their consumers with the backstory of menu items, including where food comes from, how it’s made and how it gets transported.

This study tests an adapted model built on TPB and advocates for sustainable production and consumption in line with the United Nations 2030 Agenda for Sustainable Development Goals.

This paper aims to examine the time it would take to provide medical prophylaxis for a large urban population in the wake of an airborne anthrax attack and the effect that various parameters have on the total logistical time.

A mathematical model that evaluates key parameters and suggests alternatives for improvement is formulated. The objective of the model is to minimize the total logistical time required for prophylaxis by balancing three cycles as follows: the loading cycle, the shipping cycle and the service cycle.

Applying the model to two representative cases reveals the effect of various parameters on the process. For example, the number of distribution centers and the number of servers in each center are key parameters, whereas the number of central depots and the local shipping method is less important.

Various psychological factors such as mass panic are not included in the model.

There are few papers analyzing the logistical response to an anthrax attack, and most focus mainly on the strategic level. The study deals with the tactical logistical level. The authors focus on the distribution process of prophylaxis and other medical supplies during the crisis, analyze it and identify the parameters that influence the time between the detection of the attack and the provision of effective medical treatment to the exposed population.

Sustainable building materials (SBMs) have recently been promoted to foster sustainable construction. While previous studies successfully presented the broad picture of SBM adoption, the question ‘What is the current state of SBM adoption in construction firms?’ was unanswered. Moreover, there is a lack of studies that investigate the impact of firm size on the adoption of SBMs. Therefore, this study aims to examine the level of readiness for SBM adoption in construction firms of different sizes.

Drawing on theoretical lenses and a review of previous studies, the study identified 20 factors affecting the readiness for SBM adoption. These factors were then grouped into market, organization, and employee readiness. Using the questionnaire survey, 229 valid responses were collected. The multiple pairwise comparison test showed significant differences in readiness for SBM adoption in firms of different sizes. The Fuzzy Synthetic Evaluation (FSE) analysis was then used to assess the level of readiness for SBM adoption in construction firms of different sizes.

The analysis of FSE showed that large-sized companies demonstrated the highest level of readiness for SBM adoption, followed by medium-sized and small-sized firms, respectively. These findings imply that larger construction firms may have more resources and organizational capacity to adopt SBMs. Conversely, smaller firms may require additional support or incentives to enhance their readiness for SBM adoption. It also highlights the need for targeted interventions and policies to promote SBM adoption across medium-sized and small-sized firms. Moreover, while market readiness emerged as the least critical category, the findings highlight the pivotal role of employee readiness across all firm sizes.

These findings underscore the importance of prioritizing employee readiness initiatives to facilitate the successful adoption of SBMs. Policymakers and industry stakeholders may need to focus on developing training programs and awareness campaigns tailored to employees, ensuring they are equipped with the necessary knowledge and skills. Moreover, strategies to enhance market readiness should also be explored through regulatory measures and incentives to encourage the adoption of SBMs. Additionally, fostering collaboration and networking among stakeholders can further promote market readiness and accelerate the uptake of SBMs in the construction industry.

This study aims to understand the factors affecting the continuance usage intention (CUI) of mHealth among the rural elderly.

An integrated model was proposed with the constructs derived from multiple models such as the unified theory of acceptance and use of technology, information system success model and expectation confirmation model. Data were collected from 400 participants who had prior experiences with mHealth services in Bangladesh. The research model was tested using the partial least squares method based upon structural equation modelling.

The findings indicated that system quality, performance expectancy, facilitating conditions and social influence were significant to the degree of confirmation and ultimately affect satisfaction and CUI. Surprisingly, service quality and information quality were insignificant.

This study has added in the field of knowledge by contributing some new thoughts and interpretations of continuance usage modelling for mHealth services. The findings may become beneficial for the government agencies, policymakers, mHealth systems developers and service providers.

As limited research was found on CUI of mHealth in the integrated view of rural elderly’s value, this research contributes to the extant literature by categorizing key factors that might support to proliferate the continuance usage of this service. Moreover, the contextualization of the related variables and integration of the existing model is theoretically original. Furthermore, because of a generic approach, the findings could be easily modified to assist other developing countries in the planning and up-take of mHealth.

The purpose of this study is to explore the influence of the regulatory environment on the efficiency of transparency within Islamic finance practices. It specifically examines how the determination of Shariah compliance, corporate governance and auditing standards is shaped by regulatory frameworks and their effects on the level of transparent financial reporting.

The research path was defined, and the research hypotheses were evaluated in the model using partial least squares structural equation modeling. The study collected data through structured surveys from 203 respondents.

The results of the PLS analysis demonstrate that Shari’ah compliance practices enhance transparency by making it difficult to breach ethical or social norms. These practices also infuse the presence of good corporate practices and quality audits that promote a culture of financial accountability, which is key for market and stakeholder confidence. The regulatory environment adds a critical moderating influence in these relationships by providing the oversight and enforcement capability required to ensure uniformity in the application of Shari’ah adherence and set transparency standards across borders.

The findings of this study have practical implications for those who implement policies, develop regulatory structures and study Islamic finance, underscoring the importance of achieving robust governance and regulatory frameworks. However, the study admits weaknesses, such as limited geographical coverage, reliance on preexisting data and the use of a cross-sectional analysis. Future research directions should include longitudinal and cross-comparative designs, the effects of modern technologies and the integration of qualitative methods alongside quantitative ones.

This paper aims to examine the friction and wear performance of the graphene synthesized from fruit cover plastic waste and oil palm fiber (OPF).

The graphene was synthesized by using a chemical vapor deposition method, where a copper sheet was used as the substrate. The dry sliding test was performed by using a micro ball-on-disc tribometer at various sliding speeds and applied loads.

The results show that both as-grown graphenes decrease the coefficient of friction significantly. Likewise, the wear rate is also lower at higher sliding speed and applied load. For this study, OPF is proposed as the best solid carbon source for synthesizing the graphene.

The main contribution of this study is opening a new perspective on the potentials of producing graphene from solid waste materials and its effect on the tribological performance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0486

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

The purpose of this study is to provide a comprehensive analysis on the economic relationship between trade openness and economic growth and to identify current developments, potential research area and future directions. The emphasis is on the identification of annual growth of publications, country-wise distribution, publication pattern, intellectual structure and cluster analysis of scientific production in this field.

This study used evaluative techniques, text mining approach and performance analysis to identify possible patterns and correlation and to measure the impact of authors/citations/scientific production. Further, this study used the bibliometric mapping to represent the structural features of scientific production. This study emphasized on identification of the research hotspots based on occurrence of indexed keywords, productive researchers and journals during 2000–2022. Further, cluster analysis is performed using VOS viewer to analyze the current dynamics and future direction of the association between trade openness and economic growth (Eck and Waltman, 2011). Also, co-citation analysis is used in this study to identify the relations among authors or journals or documents using citation data, whereas the bibliographic coupling/mapping is intended to analyze the citing documents. Similarly, co-word analysis is used to study the article keywords that are mainly used to assess the conceptual structure of a concerning subject.

Economic growth is a function of trade openness, and it is important to analyze the relationship between trade openness and economic growth. Trade openness tends to become more liberalized over time, to contribute more to economic growth. Empirical evidence suggested that there exists a strong association between trade openness and economic growth. Further, keyword timeline analysis illustrated that the linkage between trade openness and economic growth is current area of interest among researchers. As per bibliometric analysis, China, Pakistan and Malaysia are the three most prolific countries in the terms of published articles on this theme. However, the most influential publications based on h-index and citation on trade openness–economic growth relationship is produced by Turkey. Based on cluster analysis, this study suggests that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development.

There are some limitations of this study. The first limitation is the authors have used Scopus database, leaving the possibility for future research to use Web of Science, Google Scholar or other similar sources. The second limitation is that the authors have used search terms “trade openness “and “economic growth,” although research could be performed using synonyms or even relevant terms in other languages.

Cluster analysis suggested that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development. Therefore, this study identified the potential research area in this research domain.

To confirm the originality of this study, to the best of the authors’ knowledge, this is the first study to combine bibliometric analysis and cluster analysis on trade openness–economic growth relationship. This study makes a comparison with phenomena/processes/events in contemporary economic and social reality in the field of trade openness and economic growth relationship.

The purpose of this study was to determine whether there are differences in skin temperature under graphene-infused fleece and traditional polyester fleece materials in the interior of a wetsuit.

A total of 48 participants surfed for a minimum of 40 min in a custom wetsuit with a torso lined with graphene-infused fleece on one half and traditional polyester fleece on the other. Eight iButton thermistors were used to record skin temperatures bilaterally at the upper back, chest, abdomen and lower back every minute for the entire surf session. After surfing, participants responded to questions associated with their perception of warmth and comfort and their knowledge of fleece materials.

Skin temperatures did not differ between the two types of fleece at the upper back, chest and abdomen locations. Skin temperatures in the lower back were significantly warmer under the traditional polyester fleece compared to graphene-infused fleece. Participant responses associated with warmth were consistent with skin temperature measurements.

The results of this study indicate that a graphene-infused nylon fleece interior does not clearly influence skin temperature in surfers when compared to a traditional polyester fleece interior. While skin temperatures were significantly lower under the graphene-infused nylon fleece at the low back, the other three anatomical locations did not exhibit significant differences.

Thermoregulation is an important consideration for the safety and performance of surfers in the ocean. Evidence suggests that the inner lining of a wetsuit may impact thermoregulation while surfing; however, no prior studies have compared interior materials.