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As an important part of national governance, the online communication of education policies usually attracts the attention of many subjects, including the public and the media. Existing research mainly focuses on analysing communication behaviour of a single subject. However, with the rapid development of social media, policy information communication is often accompanied by the participation of multiple subjects and forms diversified communication behaviours and interaction patterns. The comprehensive identification of multiple subjects and their interactions can accurately depict the communication process and effectively support the efficient communication of policies. Therefore, this paper aims to conduct fine-grained analysis on the multiple subjects in information communication of the education policy.

This paper explored the communication and interaction process of the education policy via multidimensional analysis. Specifically, the authors firstly obtained multi-source communication data to identify key communication subjects. Secondly, the authors mined the communication contents generated by communication subjects to measure the diversified correlations between subjects. Finally, the authors depicted the interaction of subjects in policy information communication.

The experimental results reveal that there are multiple key subjects in the policy information communication, and the communication roles of the subjects change with the communication process, including dominance role, one-way or two-way effect role. This further indicates the need to allocate resources dynamically in the process of policy communication.

Analysing the process of policy communication and identifying the dynamic interaction between communication subjects can provide more a comprehensive and detailed decision-making basis for policy formulation and implementation. In addition, the research ideas and methods presented in this paper expand the perspective of information communication research.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

To address the shortcomings of existing academic user information needs identification methods, such as low efficiency and high subjectivity, this study aims to propose an automated method of identifying online academic user information needs.

This study’s method consists of two main parts: the first is the automatic classification of academic user information needs based on the bidirectional encoder representations from transformers (BERT) model. The second is the key content extraction of academic user information needs based on the improved MDERank key phrase extraction (KPE) algorithm. Finally, the applicability and effectiveness of the method are verified by an example of identifying the information needs of academic users in the field of materials science.

Experimental results show that the BERT-based information needs classification model achieved the highest weighted average F1 score of 91.61%. The improved MDERank KPE algorithm achieves the highest F1 score of 61%. The empirical analysis results reveal that the information needs of the categories “methods,” “experimental phenomena” and “experimental materials” are relatively high in the materials science field.

This study provides a solution for automated identification of academic user information needs. It helps online academic resource platforms to better understand their users’ information needs, which in turn facilitates the platform’s academic resource organization and services.

The purpose of this study was to examine the global perceptions of social equity in the fine dining business model as a result of the surprise announcement for the 2024 planned closure of the Michelin three-star restaurant, Noma.

This study used critical discourse analysis to inductively analyze 91 source documents retrieved through a lexical database search. The analysis yielded five overarching themes and six subthemes.

Findings from this study serve as a benchmark in retrospect for capturing a rapidly accelerating global conversation from January to March 2023 around the long-term viability and social sustainability of the fine dining business model.

Against the backdrop of labor challenges in the restaurant industry due to the Covid-19 pandemic and its aftermath, the announced closure of Noma precipitated criticism of the stage (unpaid intern) system and the intense pressures of attaining and maintaining Michelin star status.

Results from the discourse analysis suggest certification for fine dining restaurants, perhaps through the Michelin Guide, for demonstrating a commitment to social sustainability as a qualifier to achieve a Michelin star.

Findings from this research reveal a palpable change in societal tolerance for a more socially sustainable fine dining restaurant business model that advances equitable solutions for its workers while assuring the economic sustainability of restaurants.

This study drew upon a foodscape lens to reveal a juxtaposition between well-executed environmentally sustainable initiatives in the fine dining business model and the threats to the social sustainability among its workers.

The aim was not to perform a systematic review but firstly to search in PubMed, Science Direct, Scopus and Web of Science databases on the papers published in the last five years using tools for reviewing the statement of preferred information item for systematic reviews without focusing on a randomized analysis and secondly to perform a bibliometric analysis on the properties of films and coatings added of tocopherol for food packaging.

On January 24, 2022, information was sought on the properties of films and coatings added of tocopherol for use as food packaging published in PubMed, Science Direct, Scopus and Web of Science databases. Further analysis was performed using bibliometric indicators with the VOSviewer tool.

The searches returned 33 studies concerning the properties of films and coatings added of tocopherol for food packaging, which were analyzed together for a better understanding of the results. Data analysis using the VOSviewer tool allowed a better visualization and exploration of these words and the development of maps that showed the main links between the publications.

In the area of food science and technology, the development of polymers capable of promoting the extension of the shelf life of food products is sought, so the knowledge of the properties is vital for this research area since combining a biodegradable polymeric material with a natural antioxidant active is of great interest for modern society since they associate environmental preservation with food preservation.

This paper investigates the critical role of entrepreneurial computer engineers in driving innovation and accelerating economic growth through the creation of technological businesses. By analyzing their contributions to innovation ecosystems, this paper aims to provide insights into the unique impact these engineers have within the entrepreneurial landscape. The study underscores the need for tailored policies that harness the potential of entrepreneurial computer engineers to achieve macroeconomic objectives amidst ever-changing economic complexities.

To examine the significance of entrepreneurial computer engineers within the innovation ecosystem, this study uses bibliometric analysis with VOS viewer to explore existing literature on engineering and entrepreneurship.

Using bibliometric analysis, the authors reveal a network of interconnected skills such as risk-taking, self-determination and project-based learning, evident in the co-occurrence of keywords.

The entrepreneurial computer engineer plays a central role in steering technical innovation and fostering sustainable economic growth within the field of computer engineering. The authors pinpoint specific skills and strategic pathways crucial for the growth and development of entrepreneurial computer engineers, emphasizing the unique contributions and challenges within this domain.

This paper addresses the under-researched topic of engineering entrepreneurship in relation to innovation, aiming to provide knowledge and insights into the intersection of engineering and entrepreneurship. By examining this nexus, the paper contributes to filling the gap in existing literature and offers valuable perspectives for both academia and industry.

Green entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.

The study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.

Results indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.

The study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.

This study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.

Asset pricing literature is facing a credibility crisis, given debates associated with publication biases, data mining, replicability, crowding and lack of theoretic foundations. This study proposes that emerging markets (EMs), with their specific socioeconomic characteristics and lesser financial integration with developed markets (DMs), might provide useful arguments to the debate and improve our understanding of asset pricing. Beyond out-of-sample evidence for DM findings, EM research can unveil regional-specific factors overlooked by mainstream literature and investigating reasons behind differences can reveal epistemological elements for proposing and testing theories, and clarifying causal mechanisms.

The present work conducts an EM-focused systematic review, by applying the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a transparent and replicable procedure, to gather a representative collection of papers and using bibliometric methods to analyze bibliographic data.

Besides summarizing and contextualizing scientific production, revealing most important themes and actors, we confirm a clear bias toward DM and identify low scientific collaboration among EM. Additionally, we assess to which extent current studies fulfills EM research potential.

There is a home bias in literature, with most studies focusing on DM. This systematic review is exclusive to EM literature and suggests how EM research can improve literature credibility.

Teacher agency plays a crucial role in teachers’ professionalism and makes them capable of acting powerfully in their teaching context. The purpose of this study was to explore the role of case-based instruction (CBI) on the agency development of EFL (English as a foreign language) student-teachers.

The study followed a descriptive narrative design and involved ten student-teachers in five CBI sessions. The data collected through different data sources, such as narratives, interviews, recorded sessions and focused groups, were analyzed using a deductive-inductive thematic analysis.

The results showed that CBI has a constructive role in developing the agency of EFL student-teachers. Active participation in CBI sessions helps teachers consider their future desires. The exploration of cases in CBI sessions helps them recall past experiences that led to the development of their agency. Brainstorming ideas in CBI sessions helps teachers consider their beliefs in decision-making and analyze their past experiences. In conclusion, CBI can help develop teacher professionalism and acknowledgment of the importance of teacher agency.

The research has addressed student-teachers’ agency development through an ecological perspective and CBI.

This study aims to undertake a theoretical and technical exploration of the literature on Work Readiness (WR) through the implementation of a systematic literature review and bibliometric analysis. The present study addresses seven distinct research questions: (1) an examination of the descriptive features characterizing the literature on WR, (2) an analysis of trends in annual scientific publications related to WR, (3) the identification of the most pertinent and high-impact sources contributing to WR, (4) the delineation of the globally cited articles exerting the most influence on WR, (5) the determination of the most relevant countries associated with WR, (6) an evaluation of the outcomes derived from Bradford’s Law of Scattering and Lotka’s Law of scientific productivity in the context of WR, and (7) the identification of the prevailing research avenues that hold significance for future studies on WR.

The present study employed Systematic Literature Review (SLR) and bibliometric analysis mapping techniques to analyze 521 articles extracted from the Scopus database. The analysis utilized Biblioshiny software and VOSviewer software as the primary tools.

The findings reveal that WR constitutes a steadily expanding subject discipline, showcasing a notable 9.12% annual growth in scientific production spanning from 1975 to 2023. Australia, the USA, and Canada emerged as the most productive countries within the field of WR, as evidenced by their cumulative scientific production. The thematic map of keyword analysis suggests several burgeoning pathways for future researchers in the WR domain, including workplace learning, functional capacity evaluation, graduate WR, digital literacy, blended learning, resilience, and curriculum.

This study contributes to the WR discourse by providing a comprehensive literature review. The findings of this study hold significance for graduates, universities, employers, the higher education industry, and the broader community.