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This study aims to assess the accuracy of degree adaptive strategies in the context of incompressible Navier–Stokes flows using the high-order hybridisable discontinuous Galerkin (HDG) method.

The work presents a series of numerical examples to show the inability of standard degree adaptive processes to accurately capture aerodynamic quantities of interest, in particular the drag. A new conservative projection is proposed and the results between a standard degree adaptive procedure and the adaptive process enhanced with this correction are compared. The examples involve two transient problems where flow vortices or a gust needs to be accurately propagated over long distances.

The lack of robustness and accuracy of standard degree adaptive processes is linked to the violation of the free-divergence condition when projecting a solution from a space of polynomials of a given degree to a space of polynomials with a lower degree. Due to the coupling of velocity-pressure in incompressible flows, the violation of the incompressibility constraint leads to inaccurate pressure fields in the wake that have a sizeable effect on the drag. The new conservative projection proposed is found to remove all the numerical artefacts shown by the standard adaptive process.

This work proposes a new conservative projection for the degree adaptive process. The projection does not introduce a significant overhead because it requires to solve an element-by-element problem and only for those elements where the adaptive process lowers the degree of approximation. Numerical results show that, with the proposed projection, non-physical oscillations in the drag disappear and the results are in good agreement with reference solutions.

This paper aims to present the development of a holistic campus facility management (CFM) performance assessment framework that incorporates a fuzzy logic approach and integrates a comprehensive set of key factors for successful management of campus facilities. The devised framework aims to cater to the needs of campus facilities management firms and departments for the purpose of gauging and assessing their performance across different management domains. Through this approach, facility management organizations can detect potential areas of enhancement and adopt preemptive steps to evade issues, foster progress and ensure success.

After a comprehensive analysis of the literature, conducting in-depth interviews with industry experts and employing the Delphi technique in two rounds, a total of 45 indicators critical to CFM success were identified and subsequently sorted into seven distinct groups. Through an online questionnaire, 402 subject-matter experts proficiently assessed the significance of the critical success indicators and their groups. A fuzzy logic framework was developed to evaluate and quantify a firm's compliance with the critical success indicators and groups of indicators. The framework was subsequently weighted using computations of the relative importance index (RII) based on the responses received from the questionnaire participants. The initial section of the framework involved a comprehensive analysis of the firm's performance vis-à-vis the indicators, while the latter part sought to evaluate the impact of the indicators groups on the overall firm's performance.

The utilization of fuzzy logic has uncovered the significant effects each effective CFM key indicator on indicators groups, as well as the distinct effects of each CFM indicators group on the overall performance of CFM. The results reveal that financial management, communications management, sustainability and environment management and workforce management are the most impactful indicators groups on the CFM performance. This suggests that it is imperative for management to allocate increased attention to these specific areas.

This study contributes to the advancement of current knowledge by revealing vital indicators of effective CFM and utilizing them to construct a thorough fuzzy logic framework that can assist in evaluating the effectiveness of CFM firms worldwide. This has the potential to provide crucial assistance to facility management organizations, facility managers and policymakers in their quest for informed decision-making.

The impact of banking deregulation on firms and economic growth is heavily researched, but not the effects on banks’ risk-taking. This study aims to investigate the impact of China’s 2009 banking deregulation on bank risk-taking, particularly from a balance sheet capacity perspective.

Using a difference-in-differences approach, this study examines how deregulation affects bank risk-taking. A three-stage regression strategy is employed to conduct mechanism analysis.

The results reveal that deregulated banks exhibit higher levels of risk-taking. Mechanism analysis confirms the bank balance sheet capacity channel: deregulation helps strengthen the net interest margin of deregulated banks, which enhances their balance sheet capacity and subsequently increases their risk appetite. In addition, deregulation improves firms’ access to long-term credit in regions with limited credit availability, especially for smaller firms, thereby expanding the financial sector’s service outreach.

While banking deregulation enhances credit availability for firms and supports the real economy, it also raises banks’ risk-taking, posing challenges to financial stability. Our study highlights the trade-off between supporting the real economy and maintaining financial stability under banking deregulation.

This study fills a gap in research on the effects of banking deregulation on bank risk-taking, highlighting the critical role of balance sheet capacity in this process.

This study aims to examine the resilience of Peruvian startups during the COVID-19 pandemic using a framework proposed by Lengnick-Hall et al. (2011), in which resilience impacts organizational strengthening. The goal is to identify those characteristics that allowed certain startups to discover growth opportunities amid this crisis.

This study analyzed human, social and entrepreneurial capital variables in Peruvian startups using data from a survey conducted in July 2020. Binary logistic regression was used to determine which organizational resources increased the probability of identifying growth opportunities during the pandemic.

The findings suggest that human capabilities become secondary in extreme crises such as pandemics. Critical factors for startup resilience include commercial partnerships with established firms, founders’ capital investment, business maturity and adoption of advanced digital technologies.

This research provides unique insights into startup resilience and growth in Peru during the COVID-19 crisis. The authors observed that business growth during this period was largely unpredictable, with less emphasis on human capabilities. The study highlights the importance of external factors in resilience, the role of collaboration between established firms, the integration of advanced digital technologies and the influence of founders’ investments and business maturity in navigating difficult times.

Este estudio examina la resiliencia de las startups peruanas durante la pandemia de COVID-19 utilizando un marco propuesto por Lengnick-Hall et al. (2011), en el que la resiliencia tiene un efecto en el fortalecimiento de las organizaciones. Su objetivo es identificar las características que permitieron a ciertas startups descubrir oportunidades de crecimiento en medio de esta crisis.

Analizamos variables de capital humano, social y empresarial en startups peruanas utilizando datos de una encuesta realizada en julio de 2020. Se utilizó regresión logística binaria para determinar qué recursos organizativos incrementaban la probabilidad de identificar oportunidades de crecimiento durante la pandemia.

Nuestros hallazgos sugieren que las capacidades humanas pasan a un segundo plano en crisis extremas como las pandemias. Los factores críticos para la resiliencia de las startups incluyen las asociaciones comerciales con empresas establecidas, la inversión de capital de los fundadores, la madurez empresarial y la adopción de tecnologías digitales avanzadas.

Esta investigación proporciona una visión única sobre la resiliencia y el crecimiento de las startups en Perú durante la crisis COVID-19. Observamos que el crecimiento empresarial durante este período fue en gran medida impredecible, con menos énfasis en las capacidades humanas. El estudio subraya la importancia de los factores externos en la resiliencia, el papel de la colaboración con las empresas establecidas, la integración de tecnologías digitales avanzadas, la influencia de las inversiones de los fundadores y la madurez empresarial para navegar en tiempos difíciles.

Este estudo examina a resiliência das startups peruanas durante a pandemia da COVID-19 usando uma abordagem proposta por Lengnick-Hall et al. (2011), na qual a resiliência tem um efeito fortalecedor nas organizações. Seu objetivo é identificar as características que permitiram que determinadas startups descobrissem oportunidades de crescimento em meio a essa crise.

Analisamos variáveis de capital humano, social e empresarial em start-ups peruanas usando dados de uma pesquisa realizada em julho de 2020. A regressão logística binária foi usada para determinar quais recursos organizacionais aumentaram a probabilidade de identificar oportunidades de crescimento durante a pandemia.

Nossas análises sugerem que as capacidades humanas se tornam secundárias em crises extremas, como as pandemias. Os fatores essenciais para a resiliência das startups incluem parcerias comerciais com empresas estabelecidas, investimento de capital dos fundadores, maturidade dos negócios e adoção de tecnologias digitais avançadas.

Esta pesquisa fornece informações exclusivas sobre a resiliência e o crescimento de startups no Peru durante a crise da COVID-19. Observamos que o crescimento das empresas durante esse período foi amplamente imprevisível, com menos ênfase nas capacidades humanas. O estudo destaca a importância de fatores externos na resiliência, o papel da colaboração com empresas estabelecidas, a integração de tecnologias digitais avançadas e a influência dos investimentos dos fundadores e da maturidade dos negócios na superação de tempos difíceis.

The world is on the verge of entering the deglobalization age, and industrialized economies have ushered it in. However, there is still a scarcity of comprehensive and rigorous studies in this field. This research has tried to analyze the evolution and characteristics of deglobalization research.

The authors have employed bibliometric analysis for examining the existing evidence on accelerating deglobalization thinking based on a thorough analysis of articles published during a roughly 25-year span between 1996 and 2022. This study has used the TISM-P technique to study the relationship among the factors accelerating deglobalization thinking. This research reviews the articles on several dimensions of deglobalization using the “what”, “why”, “how”, “who”, “when” and “where” approaches.

The authors specify the critical factors, policy reforms, approaches and observed characteristics explored in this developing research area.

The authors have analyzed the factors accountable for rising deglobalization thinking and also suggested strategic recommendations based on the findings to minimize the adverse impact of globalization.

Although there is a wealth of literature on globalization, very little study has been done in the field of deglobalization. This is the first substantive review being done in the deglobalization domain. The contemporary research has used the bibliometric approach and the “5W and 1 H” framework to gain a comprehensive understanding of the changing paradigm.

The purpose of this paper is to explore the challenges of implementing accountable artificial intelligence (AI) systems in India, focusing on the need for algorithms to justify their decisions, especially in subjective and complex scenarios. By analyzing various government projects, documented biases and conducting empirical case studies and experiments, the study highlights the limitations of AI in recognizing the nuances of India’s unique social landscape. It aims to underscore the importance of integrating political philosophy to ensure that AI systems are held accountable within India’s sociopolitical context, urging policymakers to develop frameworks for responsible AI decision-making.

The research adopts a mixed-methods approach to address the five research questions. It begins with an extensive literature review, focusing on AI’s transformative potential, algorithmic bias and accountability in the Indian context. Data is collected from 15 AI use cases in health care, education and public safety, 13 government automated decision tools and five bias cases, including facial recognition and caste-based discrimination. Additionally, ten case studies and three experiments on ChatGPT are analyzed. Content analysis is used to interpret and categorize the data, identifying patterns and themes. Specific case studies and experiments on autocompletion in search engines further support the findings.

The study revealed significant limitations in current AI systems when applied to India’s complex socio-cultural landscape. Analyzing 15 AI applications and 13 government projects, the research identified multiple instances of algorithmic bias. Experiments with Google’s autocomplete and ChatGPT showed that these systems often reinforce social stereotypes and struggle with nuanced, subjective situations. The findings emphasize the accountability gap in AI-driven decisions, highlighting the need for rigorous oversight, particularly in welfare projects where errors could lead to severe consequences. The study recommends developing regulatory frameworks, improving AI design and raising public awareness to address these challenges.

In the context of complex societies like India, a pressing concern arises: who should assume responsibility for the repercussions stemming from algorithmic failures to comprehend subjective complexities? To this end, there exist no serious scholarly works toward which present paper tries to shed new insights. It draws upon insights from the corpus of political philosophy literature, encompassing both classical and contemporary notions of responsibility, and seeks to establish connections between these concepts and the unique sociopolitical structure of India. The work is unique in the focus of the paper and is original in the direction projected.

Facilities management (FM) has increasingly become crucial in the built environment. However, it is often overlooked as a crucial aspect of overall management. This study examined FM practices in gated communities (GCs), and challenges impeding the effective implementation of these practices.

The study used a qualitative approach involving the use of purposive sampling technique. A semi-structured questionnaire was used to collect data from the participants. Data gathered from the participants were analyzed thematically using MAX Qualitative Data Analysis (MAXQDA) Analytics Pro 2024 software.

FM in GCs played a pivotal role in ensuring the smooth operation of the GCs. These roles were vendor management, security management, maintenance and repairs, communication, tenancy agreements administration, and ensuring environmental sustainability. Non-adherence to the rules and regulations by occupants, lack of policies, unreliable vendors, lack of training and lack of funds are the major challenges FM faces in GCs.

The findings from this paper can be leveraged by stakeholders to help streamline FM activities in GCs to provide that conducive environment expected by tenants. It will also help owners of GCs obtain the maximum returns for their investments.

This paper provides information on FM practices and challenges in GCs from the Ghanaian perspective. The study adds to the literature on the emergence and growth of GCs in the African context.

The purpose of this paper is to provide evidence on the relationship between artificial intelligence (AI) and financial inclusion to achieve sustainable development goals (SDGs), an agenda set by United Nations for 2030. Financial inclusion is an enabler of 8 of the 17 SDGs. This paper emphasizes the introduction of AI in the financial sector, which is indispensable for achieving financial inclusion and plays a crucial role in the achievement of SDGs.

This study adopts qualitative research methodology to highlight the significance of AI in achieving high levels of financial inclusion in an economy. Both narrative and comparative approaches are used to provide empirical evidence for reaching the UN SDGs target through AI-assisted financial inclusion.

AI implementation in finance enables people to take part in the formal financial sector and thus, enhances economic growth and reduces poverty.

This research is limited in its data. Only five top AI applications are chosen and comparison is made between two countries only. Future research should consider it as an established concept and include more data to strengthen the evidence.

The results of this paper will help policymakers convince governments and institutions to put their efforts toward AI implementation in financial infrastructure of countries.

This research is unique in providing real-life examples and cases demonstrating the significance of AI implementation in the financial sector. Recent literature lacks evidence on the relationship of AI, financial inclusion and SDGs. This study adds to the existing literature by compiling data on top AI applications and comparing the performance of countries in achieving financial inclusion with the help of AI.

This paper aims to analyse the bibliometric characteristics of the ISO 50001 publication, map the state of the art of the research topic and identify future research issues.

This research is a bibliometric study. The data were collected from Scopus. Both performance and science mapping analysis were performed.

The research results showed the top author, paper and country of ISO 50001 publications. There are four author collaboration clusters and five country collaboration clusters. Eight research themes were mapped into four quadrants based on the density and centrality. The bibliometric coupling analysis showed six research clusters. Finally, the research issues were mapped. The implications were discussed.

This research gave several implications for researchers, practitioners and public policymakers. For researchers, the bibliometric analysis provides several research issues that can be followed up by future research. For practitioners, the bibliometric analysis showed that applied tools and methods that can assist the implementation of ISO 50001-based energy management have been developed. For public policymakers, the bibliometric analysis offered the knowledge structure on ISO 50001 that can be used in public policymaking development. The author collaboration cluster and the bibliometric coupling cluster can be used to trace the scientific information that is needed as the foundation of public policy.

Many ISO 50001 studies have been performed. However, based on the search in several main academic scientific paper databases, there is no bibliometric study on the research topic. This is the first bibliometric study on ISO 50001 publication. This study takes a holistic approach combining performance analysis and science mapping analysis that includes elaborated thematic mapping and evolution analysis.

India’s manufacturing sector employs about 12% of the labour force and contributes to about 17% of the nation’s GDP. The Indian government intends to implement several initiatives under the “Make in India” and Atma Nirbhar Bharat banners to increase the manufacturing sector’s share of the nation’s GDP to 25% by 2025. Applying lean manufacturing, green manufacturing and Six Sigma is crucial to ensure that India’s manufacturing sectors grow sustainably in international markets. This study aims to identify sustainability indicators and ascertain their respective weights to evaluate the sustainability performance of the Indian manufacturing industry.

This research identifies 25 sustainability indicators and classifies them into the triple bottom line of sustainability based on an evaluative literature review and expert opinion. The Best Worst Method was utilised to determine the weights of the sustainability indicators. The sustainability index was developed to evaluate economic, social and environmental sustainability.

The sustainability performance of a foundry in a significant Western Indian State city was assessed by applying the developed sustainability index. After the adoption of integrated lean, green and Six Sigma (LG&SS) strategies and related practices in the foundry, there has been a notable improvement of 68.03% in the economic index, 61.62% in the social index and 13.24% in the environmental index.

The proposed sustainability index is applied and evaluated specifically for assessing the sustainability performance of Indian manufacturing SMEs. It can be used to substantiate firm’s sustainability performance and also to assess the improvement in firm’s performance in economic, environmental and social dimensions after implementing various operational excellence practices. However, it cannot serve as a benchmark tool across similar companies or organisations.

The developed sustainable index can be used to analyse the company or organisation’s sustainability performance and see how various strategies have improved things. Practitioners can use this index to assess social, economic and environmental performance and focus on areas that need improvement.

The proposed sustainability index serves as a vital tool for monitoring a firm’s progress in triple bottom line (TBL) dimensions of sustainability, tracking a diverse range of indicators and encouraging sustainable organisational practices.

This study attempts to assess the economic, social and environmental performance of Indian Manufacturing SMEs by proposing a sustainability index.