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A generalization of Ascoli–Arzelá theorem in Banach spaces is established. Schauder's fixed point theorem is used to prove the existence of a solution for a boundary value problem of higher order. The authors’ results are obtained under, rather, general assumptions.

First, a generalization of Ascoli–Arzelá theorem in Banach spaces in Cⁿ is established. Second, this new generalization with Schauder's fixed point theorem to prove the existence of a solution for a boundary value problem of higher order is used. Finally, an illustrated example is given.

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In this work, a new generalization of Ascoli–Arzelá theorem in Banach spaces in Cⁿ is established. To the best of the authors’ knowledge, Ascoli–Arzelá theorem is given only in Banach spaces of continuous functions. In the second part, this new generalization with Schauder's fixed point theorem is used to prove the existence of a solution for a boundary value problem of higher order, where the derivatives appear in the non-linear terms.

Over the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.

The authors utilize an autoregressive distributed lag bounds testing estimation technique.

The results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.

Governments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.

First, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

The purpose of this paper is to analyse the metaverse platform in a social context to better understand the future of this tool in tourism cities and how this can help to improve the well-being of residents in both digital and physical scenarios.

In this paper, the current and probable developments in the metaverse, and its use in tourism cities and companies have been investigated. Moreover, this study develops, collects and examines the main metaverse definitions by expert authors and organizations as a methodology to ensure the transparency and credibility of the metaverse analysis.

Findings suggest that the fusion of the metaverse and tourism cities must create residents’ services and experiences in the new MetaTourPolis to help interact and connect citizens with the city’s institutions and companies, as well as make tourism cities more attractive, innovative, environmentally friendly and healthier places to live. Metaverse will bring new changes for residents and tourists, in fact, this virtual platform is already changing and improving the residents’ quality of life and people with disabilities in tourism cities. For instance, the metaverse platform has been implemented in Seoul, Santa Monica and Dubai MetaTourPolis to interact with their residents, including people with disabilities, to resolve bureaucratic and administrative problems, avoiding this group and the rest of the residents travelling by bus or car to the city’s institutions. In addition, several metaverse applications based on softbot tutors or metaverse virtual social centres have been developed to improve blind and impaired people, and elderly people’ quality of life, respectively.

A new concept called “MetaTourPolis” has been included to stage the relationship between tourism cities and the metaverse platform, where the fusion of metaverse and the new tourism polis of the 21st century will be at the service of citizens, tourists and companies, to create more sustainable, efficient, quantitative and environmental tourism cities.

Knowing the students' readiness for the fourth industrial revolution (4IR) is essential to producing competent, knowledgeable and skilled graduates who can contribute to the skilled workforce in the country. This will assist the Higher Education Institutions (HEIs) to ensure that their graduates own skill sets needed to work in the 4IR era. However, studies on students' readiness and preparedness for the 4IR in developing countries such as the Sultanate of Oman are still lacking. Therefore, this study investigates students' readiness level and preparedness for the 4IR. The findings of this study will benefit the HEIs policymakers, administration, faculties, departments, industries and society at large since they will be informed of the student's readiness and preparedness toward industry 4.0.

The authors adopted the measures from the same context as previous studies in this study. The questionnaire was divided into three sections; the first part described the purpose and introduction of the search with the surety to keep the data confidential. The second part consisted of demographical information like gender, education. The last parts consisted of four subsections, question items in these parts are based on the related previous study. Characteristics consisted of 14 items, knowledge consisted of 18 items related to 4IR technologies, Organizational Dimension comprised of four items related to academic programs, curriculum and training. Preparedness contained two items. The participants have rated all the items in 5-Likert scale.

Results from structural equation modeling showed that students' characteristics, knowledge of 4IR technologies and organizational dimensions significantly impact their preparedness for the 4IR. The study also found that organizational dimensions have the highest impact on students' preparedness. Furthermore, the organizational dimension significantly influences students' knowledge of 4IR technology. Moreover, students' characteristics related to 4IR are significantly affected by their knowledge of 4IR technology and organizational dimension. The findings suggest that HEIs are responsible for increasing the adoption of 4IR, and therefore organizational dimensions such as the academic programs, training, technological infrastructure and others are all critical for preparing students for a better future and should be given a priority.

This study has used academic programs and training to measure the organizational dimension. However, other important factors should be considered, such as technological infrastructure and leadership and governance of HEIs. Second, the current research depends on quantitative data, so future research should implement a mixed methodology (questionnaires, depth interviews, document analysis and focus group) to understand the factors affecting students' readiness for 4IR clearly. Finally, although the 4IR has numerous benefits, it also has challenges in its implementation, so future studies should focus on challenges encountered by different stakeholders in implementing 4IR-related technologies.

The curriculum must include mandatory courses related to IT infrastructure design, user experience programming, electronic measurement and control principles, and programming for data science. HEIs should also foster interdisciplinary knowledge by integrating IT, Engineering, Business and Sciences. Furthermore, the HEIs should develop their infrastructure to have smart campuses, labs, classrooms and libraries to make HEIs a space where knowledge can be generated and innovative solutions can be proposed. This entails HEIs offering necessary hardware, software and technical support because if the HEIs improve their technological resources, students will be capable of using 4IR-related technologies effectively.

The advancement of technology has resulted in the emergence of the Fourth Industrial Revolution (4IR), such as artificial intelligence, blockchain, robotics, cloud computing, data science, virtual reality and 3D printing. It is essential to investigate students' readiness for 4IR. However, there is no study as per researchers' knowledge talked about students readiness in HEIs in the Arab world. This study could be a basis for more research on students' perception of the 4IR covering students from various backgrounds and levels.

This review aims to provide synoptic documentation on acclaimed anecdotal plant-based remedies used by Latin America and the Caribbean (LAC) communities to manage COVID-19. The theoretical approaches that form the basis for using the anecdotally claimed phytotherapies were reviewed against current scientific evidence.

In this paper plant-based remedies for managing COVID-19 were searched on social and print media to identify testimonies of people from different communities in LAC countries. Information was extracted, evaluated and reviewed against current scientific evidence based on a literature search from databases such as Journal Storage (JSTOR), Excerpta Medica Database (EMBASE), SpringerLink, Scopus, ScienceDirect, PubMed, Google Scholar and Medline to explore the scientific basis for anecdotal claims.

A total of 23 medicinal plants belonging to 15 families were identified as phytotherapies used in managing COVID-19 in LAC communities.

The plant-based remedies contained valuable phytochemicals scientifically reported for their anti-inflammatory, antiviral, antioxidant and anticancer effects. Anecdotal information helps researchers investigate disease patterns, management and new drug discoveries. The identified acclaimed plant-based remedies are potential candidates for pharmacological evaluations for possible drug discovery for future pandemics.

Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.

A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.

Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.

The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

In addition to agriculture, energy production, and industries, potable water plays a significant role in many fields, further increasing the demand for potable water. Purification and desalination play a major role in meeting the need for clean drinking water. Clean water is necessary in different areas, such as agriculture, industry, food industries, energy generation and in everyday chores.

The authors have used the different search engines like Google Scholar, Web of Science, Scopus and PubMed to find the relevant articles and prepared this mini review.

The various stages of water purification include coagulation and flocculation, coagulation, sedimentation and disinfection, which have been discussed in this mini review. Using nanotechnology in wastewater purification plants can minimize the cost of wastewater treatment plants by combining several conventional procedures into a single package.

In society, we need to avail clean water to meet our everyday, industrial and agricultural needs. Purification of grey water can meet the clean water scarcity and make the environment sustainable.

This mini review will encourage the researchers to find out ways in water remediation to meet the need of pure water in our planet and maintain sustainability.

The purpose of this paper is twofold: to identify and map contemporary research on advanced technology implementations for problem-solving purposes in the manufacturing industry, and to further understand the organizational learning possibilities of advanced technology problem-solving in the manufacturing industry.

This paper outlines a scoping review of contemporary research on the subject. The findings of the review are discussed in the light of theories of contradicting learning logics.

This paper shows that contemporary research on the subject is characterized by technological determinism and strong solution-focus. A discussion on the manufacturing industries’ contextual reasons for this in relation to contradicting learning logics shows that a Mode-2 problem-solving approach could facilitate further learning and expand knowledge on advanced technology problem-solving in the manufacturing industry. A research agenda with six propositions is provided.

The introduction of advanced technology implies complex effects on the manufacturing industry in general, while previous research shows a clear focus on technological aspects of this transformation. This paper provides value by providing novel knowledge on the relationship between advanced technology, problem-solving and organizational learning in the manufacturing industry.