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This study investigates the impact of the fire decay phase on structural damage using the sectional analysis method. The primary objective of this work is to forecast the non-dimensional capacity parameters for the axial and flexural load-carrying capacity of reinforced concrete (RC) sections for heating and the subsequent post-heating phase (decay phase) of the fire.

The sectional analysis method is used to determine the moment and axial capacities. The findings of sectional analysis and heat transfer for the heating stage are initially validated, and the analysis subsequently proceeds to determine the load capacity during the fire’s heating and decay phases by appropriately incorporating non-dimensional sectional and material parameters. The numerical analysis includes four fire curves with different cooling rates and steel percentages.

The study’s findings indicate that the rate at which the cooling process occurs after undergoing heating substantially impacts the axial and flexural capacity. The maximum degradation in axial and flexural capacity occurred in the range of 15–20% for cooling rates of 3 °C/min and 5 °C/min as compared to the capacity obtained at 120 min of heating for all steel percentages. As the fire cooling rate reduced to 1 °C/min, the highest deterioration in axial and flexural capacity reached 48–50% and 42–46%, respectively, in the post-heating stage.

The established non-dimensional parameters for axial and flexural capacity are limited to the analysed section in the study owing to the thermal profile, however, this can be modified depending on the section geometry and fire scenario.

The study primarily focusses on the degradation of axial and flexural capacity at various time intervals during the entire fire exposure, including heating and cooling. The findings obtained showed that following the completion of the fire’s heating phase, the structural capacity continued to decrease over the subsequent post-heating period. It is recommended that structural members' fire resistance designs encompass both the heating and cooling phases of a fire. Since the capacity degradation varies with fire duration, the conventional method is inadequate to design the load capacity for appropriate fire safety. Therefore, it is essential to adopt a performance-based approach while designing structural elements' capacity for the desired fire resistance rating. The proposed technique of using non-dimensional parameters will effectively support predicting the load capacity for required fire resistance.

The fire-resistant requirements for reinforced concrete structures are generally established based on standard fire exposure conditions, which account for the fire growth phase. However, it is important to note that concrete structures can experience internal damage over time during the decay phase of fires, which can be quantitatively determined using the proposed non-dimensional parameter approach.

This paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.

In this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.

The main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.

It is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

The purpose of the study is to analyse the impact of COVID-19 on the hospitality industry during the rise of worldwide pandemic crises using Twitter analysis. The study is based on 57,794 English-language tweets mined from Twitter from 1 April 2020 to 15 October 2020. Based on thematic and sentiment analysis, the study found that overall sentiments expressed on Twitter were negative. This chapter contributes to existing knowledge about the COVID-19 crisis and broadens the respondents’ understanding of the potential impacts of the crisis on the most vulnerable tourism and hospitality industry. This research emphasises the sustainable revival of the hospitality industry.

This study intends to conceptually and technically examine the literature on work integrated learning (WIL) through a systematic literature review and bibliometric analysis. The present study addresses eight distinct research questions: (1) descriptive features of the extracted literature on WIL, (2) publications trends and thematic evolution in the field of WIL, (3) the most relevant and high-impact sources on WIL, (4) the most global cited articles on WIL, (5) the most relevant and high-impact authors on WIL, (6) the most relevant countries on WIL, (7) outcomes of Bradford’s Law of Scattering and Lotka’s Law of Scientific Productivity and (8) trending research avenues for future studies in the field of WIL.

The present study employed systematic literature review (SLR) and bibliometric analysis mapping techniques to analyze 1,295 articles extracted from the Scopus database. The analysis utilized Biblioshiny software and VOSviewer software as the primary tools.

The findings reveal that WIL constitutes a steadily expanding subject discipline, showcasing a notable 23.28% annual growth in scientific production spanning from 2002 to 2023 (July). Australia, South Africa and Canada emerged as the most productive countries within the field of WIL, as evidenced by their cumulative scientific production. The thematic map of keyword analysis suggests several burgeoning avenues for future researchers in the WIL domain, including education, reflective practices, curriculum, employability skills, international students, learning and self-efficacy.

This study contributes to the WIL discourse by providing a comprehensive literature review. The present study’s findings hold significance for graduates, universities, employers, the higher education industry, policymakers, regulators and the broader community.

While previous operations management literature acknowledges the positive influence of Lean and Industry (I4.0) on performance, recent studies examining the synergy between these two factors have produced inconsistent and contradictory results. Therefore, this study aims to provide a comprehensive understanding of the effect of Lean and I4.0 synergy on firm performance.

This study utilised a meta-analysis approach, examining 23 empirical studies exploring multiple effects of the Lean and I4.0 synergy on firm performance. Multiple subgroup analyses were conducted to assess the contradictory outcomes and identify in what conditions such synergy may achieve performance.

The results affirm the prevailing positivist perspective among most scholars regarding the positive influence of the Lean and I4.0 synergy on firm performance. However, the overall effect size derived from the studies indicates a weak relationship, suggesting that this synergy alone is not the sole determinant factor of firm performance. In addition, the subgroup analyses reveal the presence of contingent conditions that may affect the performance outcomes when integrating Lean and I4.0, as most effects exhibit a weak relationship.

This study represents the first meta-analysis investigating the relationship between the Lean and I4.0 synergy on firm performance. By shedding light on the contradictory effects often depicted in the operations management literature, this study provides a critical reflection for researchers who tend to adopt an overly optimistic view of such synergy.

The purpose of this study is to determine whether the Ottoman Empire’s net interest payments and foreign debt were sustainable or not in terms of their burden on budget revenues, using the method of historical econometric analysis.

In this study, the period between 1847 and 1882 of the Ottoman Empire is analyzed for sustainability analysis. Within the framework of the study, unit root tests and econometric analysis methods frequently used in the literature were used to analyze the sustainability of public debt. In the econometric analysis, in addition to various unit root tests, current econometric analysis methods, in particular Fourier expansion, were also used.

The results of econometric analyses showed that the burden of interest payments and foreign debt on the budget of the Ottoman state was unsustainable. This situation clearly shows the reason for the official bankruptcy of the Ottoman Empire, which was declared in 1875.

Although this study reveals the bankruptcy process of an important structure such as the Ottoman Empire in the historical process through econometric analyses, it also gives a very important message to today’s states. Accordingly, today’s state policies and decision-making mechanisms should take these results into account and strive to make the burden of public interest payments sustainable. It is believed that the study will shed light on the public finance policies of today’s states by drawing lessons from the collapse process of the Ottoman state.

Unlike the historical assessments in the literature on the decline of the Ottoman Empire, this study presents a cliometric approach by applying current econometric analysis techniques to past historical data. The study explains the unsustainability of the Ottoman Empire’s interest payments and external debt burden in the period under consideration in a way that, to the best of the authors’ knowledge, has not been done before.

The purpose of this paper is twofold: first, to present a rigorous bibliometric analysis and a systematic literature review of the critical success factors (CSFs) for Building information modelling (BIM)-based digital transformation; second, to identify the relationship between the dimensions in favour of BIM implementation.

This study adopts a two-step approach to combine bibliometric and systematic literature review to explore the research topic of BIM and CSFs. Bibliometric tools such as Biblioshiny in R language and Ucinet software were applied to this study.

Besides identifying the two most influential authors (e.g. Bryde and Antwi-Afari), the key journal for disseminating articles, and the most influential countries in this discourse (e.g. Hong Kong and Australia), the study also identifies four pivotal research themes derived from the co-occurrence analysis of keywords: the fusion of sustainability and technology with BIM; practical application and its integration within construction management; innovation and engineering paradigms; and the advent of emerging technologies (e.g. Blockchain) within developing nations. Additionally, the paper introduces a comprehensive framework for selecting CSFs pertinent to BIM-centred digital transformation as viewed through the lens of dynamic capabilities.

This paper establishes a link between dynamic capabilities theory, CSFs, and BIM dimensions, presenting a multifaceted framework guiding future paths and offering practical insights for managerial and political decision-makers engaged in digital transformation endeavours. The study positions dynamic capabilities as pivotal, aligning digital technologies with continuous business performance, and advocates for a strategic focus on digital transformation.

Prefabricated columns connected by grouted sleeves are increasingly used in practical projects. However, seismic fragility analyses of such structures are rarely conducted. Seismic fragility analysis has an important role in seismic hazard evaluation. In this paper, the seismic fragility of sleeve connected prefabricated column is analyzed.

A model for predicting the seismic demand on sleeve connected prefabricated columns has been created by incorporating engineering demand parameters (EDP) and probabilities of seismic failure. The incremental dynamics analysis (IDA) curve clusters of this type of column were obtained using finite element analysis. The seismic fragility curve is obtained by regression of Exponential and Logical Function Model.

The IDA curve cluster gradually increased the dispersion after a peak ground acceleration (PGA) of 0.3 g was reached. For both columns, the relative displacement of the top of the column significantly changed after reaching 50 mm. The seismic fragility of the prefabricated column with the sleeve placed in the cap (SPCA) was inadequate.

The sleeve was placed in the column to overcome the seismic fragility of prefabricated columns effectively. In practical engineering, it is advisable to utilize these columns in regions susceptible to earthquakes and characterized by high seismic intensity levels in order to mitigate the risk of structural damage resulting from ground motion.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.