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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.

In today’s world, empowering individuals, promoting social cohesion and advancing economic development all hinge on access to high-quality education, prioritizing diversity, inclusion and equality. Rethinking current educational strategies using cyber-physical learning assets is necessary to accommodate the learning inclusivity and equity and escalating demands of a globalized world. There is a pressing demand for evidence to support the efficacy of collaborative learning in transforming curriculum and fostering learner inclusion. However, it is recognized as a pedagogical technique within the quality education domain. This study aims to address this knowledge gap by investigating how hybridized cybergogy paradigms facilitate collaborative learning, focusing on diversity, equity and inclusion, to improve educational quality in higher education.

This study used a qualitative approach with an exploratory design guided by an interpretive philosophical perspective. The data was gathered from 60 prospective teachers from the public sector university of Sindh, Pakistan. Semi-structured interviews were conducted with participants. They were then analyzed using theme analysis to understand their views on the potential of hybridized cybergogy paradigms for collaborative learning to improve the quality of education provided at institutions.

The study results confirm that learners benefit from increased access to learning resources, improved critical thinking and problem-solving skills and a more diverse and inclusive classroom working together in a collaborative hybridized cybergogy setting. By fostering SDG 4 (Quality Education) and the 21st-century skills necessary for global marketplace engagement and competing in progressive environments, this creative method equips learners with the capabilities to face modern global challenges.

The study offers valuable practical suggestions to stakeholders in higher education, including faculty, policymakers and teacher education programs, for integrating hybridized cybergogy and collaborative learning to align curricula with sustainable development goals. Additionally, it bridges a significant gap in the existing literature, which will aid future researchers interested in exploring this area.

This study stands out as it explores an underexamined area while providing novel educational insights.

The US Federal Government awards contracts worth hundreds of billions of dollars each year. Many firms that rely on these contracts have appointed former government officials to their corporate boards in the hopes of securing government contracts. The purpose of this paper is to examine the relationship between these government experienced directors (GEDs) on boards and firms being awarded government contracts.

The paper compiles a panel data set from 2017 to 2020 for S&P 500 firms. This includes hand-collected data for government-experienced directors on boards. This is tested using both regression and analysis of variance methodologies.

Results find that former government officials on corporate boards increase the amount of government contracts secured by the firm, both in absolute terms and as a percentage of firms’ revenue. There are significant industry level effects for the health care and financials sectors. Government-experienced directors on boards are also positively related to firms receiving COVID contracts. Lobbying was not found to be related to the securing of regular government contracts but was positively related to firms obtaining COVID contracts.

This paper contributes to the literature by using panel data, an expanded definition of GEDs and data on COVID contracts. The “revolving door” between government and firms is paying off for companies.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This paper aims to analyse the influence of workforce diversity on the firm’s likelihood to develop organisational innovations. Operationalising human resources diversity is not straightforward, and its effect has been rather overlooked in the context of non-technological innovations. This study analyses the impact of task-related diversity among research and development (R&D) unit workers and women R&D workers, in particular.

To estimate the impact of task-related diversity on firm propensity to undertake organisational innovation, this study uses a generalised linear model (GLM) – with a binomial family and log–log extension. GLMs are used to control problems of over-dispersion, which, in models with binary response variables, could generate inaccurate standard error estimates and provide inconsistent results.

This paper provides three important results. Firstly, employee diversity increases the firm’s propensity to engage in organisational innovations. Secondly, the influence of each facet of task-related diversity varies depending on the type of organisational innovation considered. Thirdly, gender has an effect on the innovation process; this study shows that women play a different role in the production of non-technological innovations.

This paper makes several contributions to the literature. Firstly, it makes a theoretical contribution to research on innovation management by considering the influence of human resources diversity on the development of non-technological innovations. Secondly, this study analyses the role of workforce diversity in an R&D department context to clarify the contribution made by women R&D workers.

This study aims to investigate the impact of stakeholders’ nonfinancial resources (NFRs) on companies’ profitability, filling a significant gap in the literature regarding the role of NFRs in value creation.

Data from 76 organizations from 2017 to 2019 were collected and analyzed. Four primary NFRs and their key value drivers were identified, representing core elements that support different dimensions of a company’s performance. Statistical tests examined the relationship between stakeholders’ NFRs and financial performance measures.

When analyzed collectively and individually, the results reveal a significant positive influence of stakeholders’ NFRs on a firm’s profitability. Higher importance assigned to NFRs correlates with a higher return on sales.

This study contributes to the literature by empirically bridging the gap between stakeholder theory and the resource-based view, addressing the intersection of these perspectives. It also provides novel insights into how stakeholders’ NFRs impact profitability, offering valuable implications for research and managerial practice. It suggests that managers should integrate nonfinancial measures of NFRs within their performance measurement system to manage better and sustain companies’ value-creation process.