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The primary purpose of this research is to identify and compare the multifractal behavior of different sectors during these crises and analyze their implications on market efficiency.

We used multifractal detrended fluctuation analysis (MF-DFA) to analyze stock returns from various sectors of the Moscow Stock Exchange (MOEX) in between two significant periods. The COVID-19 pandemic (January 1, 2020, to December 31, 2021) and the Russia–Ukraine conflict (RUC) (January 1, 2022, to June 30, 2023). This method witnesses multifractality in financial time series data and tests the persistency and efficiency levels of each sector to provide meaningful insights.

Results showcased persistent multifractal behavior across all sectors in between the COVID-19 pandemic and the RUC, spotting heightened arbitrage opportunities in the MOEX. The pandemic reported a greater speculative behavior, with the telecommunication and oil and gas sectors exhibiting reduced efficiency, recommending abnormal return potential. In contrast, financials and metals and mining sectors displayed increased efficiency, witnessing strong economic performance. Findings may enhance understanding of market dynamics during crises and provide strategic insights for the MOEX’s investors.

Understanding the multifractal properties and efficiency of different sectors during crisis periods is of paramount importance for investors and policymakers. The identified arbitrage opportunities and efficiency variations can aid investors in optimizing their investment strategies during such critical market conditions. Policymakers can also leverage these insights to implement measures that bolster economic stability and development during crisis periods.

This research contributes to the existing body of knowledge by providing a comprehensive analysis of multifractal properties and efficiency in the context of the MOEX during two major crises. The application of MF-DFA to sectoral stock returns during these events adds originality to the study. The findings offer valuable implications for practitioners, researchers and policymakers seeking to navigate financial markets during turbulent times and enhance overall market resilience.

This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis.

This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations.

The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks.

This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector.

This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.

This study aims to solve the problem that both the speed and the required driving power of electric vehicles (EVs) will change during the dynamic wireless charging (DWC) process, making it difficult to charge EVs with a constant power considering the overall efficiency of DWC system, the numbers of EVs and the power supply capacity. Therefore, this paper proposes the power control and efficiency optimization strategies for multiple EVs.

The wireless power charging system for multiple loads with a structure of double-sided LCC compensation topology is established. The expressions of optimal transmission efficiency and optimal equivalent impedance are derived. Taking the Tesla Model 3 as an example, a method to determine the number of EVs allowed by one transmitter coil and the overall charging power is proposed considering EV speed, power supply capacity, safe braking distance and overall efficiency. Then, the power control strategy, which can adapt to the changes of EV speed and the efficiency optimization strategy under different numbers of EVs are proposed.

In this paper, a method to determine the numbers of EVs allowed by one transmitter coil and the overall charging power is proposed considering EVs speed, power supply capacity, safe braking distance and overall efficiency. The accuracy of the charging power is good enough and the overall efficiency reaches a maximum of 91.79% when the load resistance changes from 5Ω to 20Ω.

In this paper, the power control and efficiency optimization strategy of DWC system for multiple EVs are proposed. Specifically, a method of designing the number of EVs and charging power allowed by one transmitter coil considering the factors of EV speed, power supply capacity, safe braking distance and overall efficiency is designed. The overall efficiency of the experiment reaches a maximum of 91.79% after adopting the optimization strategy.

The purpose of this paper is to understand if and how industrialized house building (IHB) could support productivity developments for housebuilding on project and industry levels. The take is that fragmentation of construction is one explanation for the lack of productivity growth, and that IHB could be an integrating method of overcoming horizontal and vertical fragmentation.

Singe-factor productivity measures are calculated based on data reported by IHB companies and compared to official produced and published research data. The survey covers the years 2013–2020 for IHB companies building multi-storey houses in timber. Generalization is sought through descriptive statistics by contrasting the data samples to the used means to control vertical and horizontal fragmentation formulated as three theoretical propositions.

According to the results, IHB in timber is on average more productive than conventional housebuilding at the company level, project level, in absolute and in growth terms over the eight-year period. On the company level, the labour productivity was on average 10% higher for IHB compared to general construction and positioned between general construction and general manufacturing. On the project level, IHB displayed an average cost productivity growth of 19% for an employed prefabrication degree of about 45%.

Empirical evidence is presented quantifying so far perceived advantages of IHB. By providing analysis of actual cost and project data derived from IHB companies, the article quantifies previous research that IHB is not only about prefabrication. The observed positive productivity growth in relation to the employed prefabrication degree indicates that off-site production is not a sufficient mean for reaching high productivity and productivity growth. Instead, the capabilities to integrate the operative logic of conventional housebuilding together with logic of IHB platform development and use is a probable explanation of the observed positive productivity growth.

The performance of large-scale projects is often challenged due to major environmental changes that occur during their life. However, literature has paid little attention to the governance adaptations required to respond effectively to these changes. This paper aims to study changes in the project environment over time, the corresponding governance adaptations and their impact on project performance.

To ensure triangulation between two sources of evidence, we used both primary and secondary data sources and examined 14 projects through 2 studies, the first focused on seven documented, illustrative case projects and the second on interviews with senior and project managers involved in seven additional projects.

We found the key environmental changes that should trigger appropriate governance adaptations to be market evolutions, technological advancements and sociopolitical events. However, we also found that these necessary governance adaptations are not commonly implemented timely, sufficiently or effectively.

The paper distills the dynamics of large-scale projects in achieving project effectiveness and raises theoretical propositions on the combination of environmental changes and deficient governance adaptations that, over time, turns efficient projects into ineffective projects and discusses implications for theory and practice.

This study aims to evaluate the enhancement in prosthetic supply chain capabilities resulting from the implementation of additive manufacturing (AM) technologies. The study presents an emerging model outlining the key areas that undergo changes when integrating 3D printing technologies into the prosthetic supply chain.

Employing a qualitative approach, data were collected through field observations and 31 in-depth interviews conducted within various Jordanian organizations associated with the prosthetic industry and 3D printing technologies.

The findings suggest that the adoption of 3D printing technologies improves the prosthetic supply chain’s capabilities in terms of customization, responsiveness, innovation, environmental sustainability, cost minimization and patient empowerment. The study sheds light on the specific areas affected in the prosthetic supply chain following the adoption of 3D printing technologies, emphasizing the overall improvement in supply chain capabilities within the prosthetic industry.

This study provides recommendations for governmental bodies and prosthetic organizations to maximize the benefits derived from the use of 3D printing technologies.

This study contributes as the first of its kind in exploring the impact of 3D printing technology adoption in the Jordanian prosthetic industry, elucidating the effects on the supply chain and identifying challenges for decision-makers in an emerging market context.

This study aims investigate in-service teachers’ perspectives on the integration of ChatGPT, an artificial intelligence (AI)-driven chatbot, into United Arab Emirates (UAE) private schools. As the UAE progresses towards a knowledge-based economy, aligning with the goals of the UAE 2030 vision, this research assesses the capacity of ChatGPT to enhance the educational experience within the framework of technological pedagogical content knowledge.

A mixed-methods approach is used, combining a survey assessing teachers’ attitudes and a thematic analysis of open-ended responses, to explore the effectiveness, challenges and pedagogical implications of ChatGPT’s use in the classroom.

Findings reveal that teachers value ChatGPT for its potential to individualize learning and streamline the creation of educational materials, aligning with the shift towards student-centred approaches and the demands of 21st-century skills. However, significant challenges are noted, including ethical concerns, the need for reliable content and a necessity for extensive professional development to fully realize ChatGPT’s benefits.

While ChatGPT transforms teaching and learning practices, realizing this potential requires addressing critical issues through adaptive policy-making, continuous educator training and thoughtful integration into the curriculum.

The study highlights the importance of a collaborative approach to dealing with the details of AI in education, ensuring that advancements like ChatGPT align with the evolving educational paradigms of the UAE.

This paper identifies the critical success factors (CSFs) of virtual hotel operator (VHO) in using hotel management system partnerships with small- and medium-sized hotels (SMSHs).

This study uses a qualitative approach, with 25 semi-structured interviews with hotel owners and VHO management. Thematic analysis is used to determine themes to evaluate hotel owners and operators' perceptions.

CSFs for VHO partnership with SMSHs include marketing and promotion strategies, client relationships, training and human resources development, hotel operation management, innovation strategies, capital expenditures and property management systems (PMSs). VHOs also have a symbolic impact on the mutualistic relationship with SMSHs by increasing service and enhancing product competitiveness and profitability.

Findings are beneficial for VHO in determining the most significant CSFs, thereby establishing additional metrics in business performance and increasing resilience in the accommodation sector. Further studies can measure the digital technology factors from VHO, including PMSs and mobile applications.

This study first identifies CSFs for VHO companies from the perspectives of hotel owners and management. This contribution adds to the literature on CSFs in the context of digital technology implementation in SMSHs. Moreover, implications are beneficial for VHO management in determining the most significant CSFs for companies to measure the business performance of the companies and increase resilience in the accommodation sector.

As a new type of spinning machine, the jet spinning machine absorbs the carding system of the rotating cup spinning series and the nozzle part of the jet spinning. This paper aims to intends to introduce the double carding structure currently studied by the rotating cup spinning into the jet spinning machine, and analyze the influence of the nozzle characteristic number on the flow field in the double carding structure to verify the advantages of the double carding structure.

The simulation is used to evaluate the performance of single/double split jet spinning and nozzle feature number, verify the technical advantages of double split jet spinning and evaluate the influence of nozzle feature number on flow field. The influence of the nozzle characteristic number on the flow pattern in the four models is compared. The advantages and disadvantages of a conventional single comb and a double comb with a bypass channel on the longer side of the transport channel as an additional air supply channel are also evaluated.

At present, the double comb technology of rotary cup spinning is being studied at home and abroad to improve the spinning quality and improve the difficult problem of mixed yarn with large difference in processing fiber properties. At present, the jet spinning machine combines the advantages of rotary cup spinning and jet spinning, absorbing the comb system of rotary cup spinning series and the nozzle part of jet spinning. Therefore, it is found that the introduction of the double-split structure into the wool jet spinning has research value to improve the spinning quality.

The purpose of this paper is to refer to the previous research on the double comb structure in rotary spinning, and to apply the double comb structure in the new jet spinning machine to improve the spinning quality. The simulation is used to evaluate the performance of single/double split jet spinning and nozzle feature number, verify the technical advantages of double split jet spinning and evaluate the influence of nozzle feature number on flow field.

This study aims to measure the degree of volatility comovement between stock market liquidity and informational efficiency across Asia, Europe, North-South America, Africa, and the Pacific Ocean over three decades. In particular, the authors analyze the extent of the time-varying nexus between different aspects of stock market liquidity and multifractal scaling properties of the stock return series across various regions and diversified market conditions. This study further investigates several factors altering the degree of dynamic conditional correlations (DCCs) between the efficiency and liquidity of the domestic stock markets.

The study measures five aspects of stock market liquidity – tightness, depth, breadth, immediacy, and adjusted immediacy. The authors evaluate the multifractal scaling properties of the stock return series to measure the level of stock market efficiency across the regions and diversified market conditions. The study uses the dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity framework to quantify the degree of volatility comovement between liquidity and efficiency over the period.

The study finds the presence of stronger volatility comovement between inefficiency and illiquidity due to the price impact characteristics of the stock markets irrespective of different regions and diversified market conditions. The extent of time-variation increased following the shock periods, indicating the significant role of the financial crisis in increasing the volatility comovement between inefficiency and illiquidity. The highest degree of time-varying correlation is observed in the developed stock markets of Northwestern and Northern Europe compared to the regional and emerging counterparts. On the other hand, weak DCCs are observed in the emerging stock markets of Europe.

The output of the present study assists investors in identifying diversification opportunities across the regions. Additionally, the study has significant implications for market regulators, aiding in predicting future troughs and peaks. The prediction, in turn, helps formulate capital market development plans during dynamic economic situations.