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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.

Although separate studies on the influence of corrosion and fire exposure on the constitutive relationship of concrete and steel have been done, there is still a gap in knowledge on the influence of corrosion-temperature superimposition as nonlinear phenomenon. The current study is focused to investigate the response of hot-rolled steel bars subjected to corrosion-temperature superimposition.

Using the accelerated corrosion-impressed-current technique, hot-rolled specimens with different levels of corrosion were obtained. The hot-rolled rebars were first corroded to target levels such as (6, 12, 18, 24, 30 and 36%) and subsequently subjected to target temperatures (250 °C, 400 °C, 550 °C, 800 °C and 950 °C), before tensile tests were carried out to evaluate the residual mechanical response.

The outcomes showed a significant decline in the parameters governing the mechanical properties of steel reinforcement due to the combined damage due to corrosion and fire. Corroded reinforcement still showed ductile failure after exposure to fire. Moreover, the combined loss of load-bearing characteristics due to corrosion and fire has little influence on the modulus of elasticity. The outcomes of this investigation provide a theoretical database for the assessment of aged structural elements exposed to combination after exposure to fire.

The information concerning structural material's response to corrosion-temperature combined damage is still limited. The cover of the reinforcement is designed to safeguard the reinforcing bars from foreign agencies but is often damaged and spalled off due to corrosion, rendering the reinforcing bars directly exposed. The study aims at the experimental production of fire conditions in a corrosion-damaged infrastructure to cover the aforementioned research gap. The effects of corrosion being superimposed by exposure to elevated temperatures on key parameters affecting mechanical behavior were examined.

1. Influence of corrosion-temperature superimposition on the mechanical properties of hot-rolled rebars.

2. Influence of corrosion-temperature superimposition on the macro and microstructure properties of hot-rolled rebars.

3. Influence of corrosion-temperature superimposition on stress-strain curves of hot-rolled rebars.

4. Influence of corrosion-temperature superimposition on tensile strength, modulus of elasticity and elongation of hot-rolled rebars.

Influence of corrosion-temperature superimposition on the mechanical properties of hot-rolled rebars.

Influence of corrosion-temperature superimposition on the macro and microstructure properties of hot-rolled rebars.

Influence of corrosion-temperature superimposition on stress-strain curves of hot-rolled rebars.

Influence of corrosion-temperature superimposition on tensile strength, modulus of elasticity and elongation of hot-rolled rebars.

The aim of the current study is to inspect the influence of high temperatures on the compressive and split-tensile-strength (STS) of concrete mixtures produced by replacing natural river sand with waste-foundry sand (WFS) at 25%, 50%, 75% and 100%. When the experimental findings and the projected outcomes were compared by IS:456-2000 code equations, the STS results predicted by the suggested mathematical equations exhibit lower variations. It is proposed to employ the presented mathematical formulas to evaluate the STS of concrete cylindrical specimens at higher temperatures.

After fabricating, concrete mixtures were allowed to cure for 28 days. For the purpose of avoiding explosive spalling during the heating process, concrete samples are taken out from the curing chamber after 28 days and allowed to dry for two days. The manufactured concrete specimen is exposed to 100 °C, 200 °C, 300 °C, 400 °C, 500 °C and 600 °C temperatures for a duration of 2 h. After the specimens have cool down to room temperature (RT), the physical test, ultrasonic-pulse-velocity (UPV) test, compressive strength test and STS test are carried out.

With an increase in WFS content, concrete specimens' residue compressive-strength and STS decreases. The STS of samples declines as the WFS content rises with increase in temperature interval. According to the UPV test, the concrete samples quality is “good” up to 400 °C; after 500 °C, it ranges from “doubtful to poor.” The UPV values of various mixes declined as the temperature increased. Mass losses increase with exposure to greater temperatures and with an increase in the proportions of WFS in concrete specimens. For mixtures MWFS-0, MWFS-1, MWFS-2, MWFS-3 and MWFS-4 (0%, 25%, 50%, 75% and 100% WFS content), no cracks were present on any of the samples below 400 °C. Concrete surfaces start to show cracks whenever the intervals of temperature increase above 400 °C.

In this investigation, WFS elements are totally substituted for natural sand in concrete mixtures. The residue strength properties, including residual compressive strength and residual STS, were found to be lower after exposures to greater temperature when comparisons were made to referral mixtures. When comparing specimens’ compressive strength, higher temperatures have more effects on the STS of samples with higher WFS contents.

The purpose of this study is to examine knowledge management (KM) infrastructure and processes on automobile manufacturing firm innovative performance through the mediating role of agile project management (APM) practice.

The data collection involved purposive and convenience sampling techniques to gather information from 692 employees employed in various public and private automobile manufacturing firms operating in Pakistan. To test the hypothesis, data analysis was conducted using Smart PLS software version 4, using the partial least squares and structural equation modeling technique.

The result revealed that knowledge management infrastructure and processes has a positive and significant effect on firm innovative performance. Moreover, agile project management practices positively and significantly mediate the relationship between knowledge management infrastructure and processes and firm innovative performance.

The performance of high-tech automobile manufacturing firms can be enhanced by implementing agile project management practices, especially when stimulated by external factors such as innovation. In an increasingly dynamic environment, innovation acts as a favorable factor that amplifies the positive impact of agile methodologies on firm performance.

Researchers can use these findings to identify knowledge gaps that need to be addressed in future studies and understand how strategies relate to processes within the KM-APM framework. This study provides practitioners with insights on applying KM practices in an APM context to enhance knowledge performance. Practitioners can use the framework to plan KM activities that support corporate strategy across all organizational layers, ensuring the appropriate knowledge is conveyed at each level.

The recent COVID-19 pandemic caused a severe economic downturn. Employees working in these organisations face employment uncertainty. The pandemic disrupted their daily routines, and it added a layer of complexity to the already resource-constrained environment. During these times, employees would conserve their resources to maintain competitiveness, one of which is knowledge hiding. While economic activities are resuming, the appearance of new variants could mean the transition towards endemicity could be put on hold. Hence, there is a need to rethink the behaviour of employees as they would have elevated levels of anxiety towards resuming daily work activities. Therefore, this study aims to address the question of understanding employees’ perspectives toward knowledge sharing and knowledge hiding.

Drawing on the conservation of resources theory, social learning theory and the social exchange theory (SET), a conceptual framework involving ethical leadership was developed to examine if knowledge hiding or knowledge sharing behaviour is a resource for employees during these times. The partial least squares method of structural equation modelling was used to analyse results from 271 white-collar employees from Singapore.

The results show that ethical leadership encourages knowledge sharing but does not reduce knowledge hiding. At the same time, knowledge hiding, not knowledge sharing, improves one’s perception of work performance. Additionally, psychological safety is the key construct that reduces knowledge hiding and encourages sharing behaviour.

Overall, this study extends the theories, demonstrating that, first and foremost, knowledge hiding is a form of resource that provides employees with an added advantage in work performance during the endemic. At the same time, we provide a new perspective that ethical leaders’ demonstration of integrity, honesty and altruism alone is insufficient to encourage knowledge sharing or reduce knowledge hiding. It must lead to a psychologically safe environment.

This systematic review aims to identify the key determinants of knowledge transfer (KT) activities among researchers.

This study systematically reviewed KT literature in academic settings from 1995–2023. The authors searched Web of Science and Scopus using predefined keywords, following PRISMA guidelines for screening and eligibility assessment. From 158 selected articles, the authors extracted data and conducted a descriptive analysis to map KT activities’ evolution. A narrative synthesis approach categorized determinants of researchers’ KT activities.

The systematic review findings revealed a general conceptual framework that categorizes the identified determinants of KT into four categories. At the individual level, the factors are related to the sociodemographic characteristics of the researcher (e.g. gender, age, experience), their psychological aspects (e.g. attitude, intrinsic motivation, intention) and personal characteristics (e.g. self-efficacy, communication skills). At the research team level, leadership style and team dynamics. At the organizational level, the findings emphasize university characteristics (e.g. size, structure and ranking), KT culture installed and university resources. At the inter-organizational level, the key determinants were funding sources, network strength and trust.

The studies included in our database were different in terms of contexts, country of the study, the disciplines of KT and the types of KT activities examined. This variety restricts the direct comparison of research findings thus the generalizability of our conclusions. Future research should focus on specific contexts, disciplines, countries or types of KT activities to provide generalizable findings.

A better understanding of all the factors influencing KT among university researchers is essential for several reasons. First, it will enable the government to develop effective policies to promote KT ecosystems. Second, universities can create strategies, policies and programs to support researchers’ engagement in KT activities. Finally, researchers can be more strategic in their KT efforts.

This systematic review contributes to the literature by providing a comprehensive conceptual framework that identifies KT determinants at different levels and fills a gap in the existing literature that only addresses specific aspects of KT determinants. This framework can be a theoretical reference for future empirical studies. Furthermore, it practically provides recommendations for different actors including, government, universities and researchers.

This research comprehensively analyses the profound impact of Digital Transformation and Process Innovation (DT&PI) on business models (BMs) in the Food Service Sector (FSS), especially in the post-pandemic context. The study is guided by three primary research questions: (1) Identifying key FSS players and their interconnections, (2) Understanding the differentiation strategies these entities employ and (3) Assessing how COVID-19 has altered their BMs.

The study utilises a rigorous methodology, starting with a thorough analysis of the Business Model Canvas (BMC) for 100 prominent Spanish FSS firms, culminating in a comprehensive sector-wide BMC. Cluster analysis is then applied to group firms based on common attributes and relationships identified in the overall BMC. Additional insights are gathered through semi-structured interviews with representatives from FSS companies.

The study identifies five distinct clusters of FSS companies, each defined by unique BM strategies. These strategies mainly focus on sales and distribution channels, differentiating between those using multiple channels and those solely relying on digital platforms. Importantly, the study shows that digital transformation in the FSS was already in progress before the pandemic but was greatly expedited by it. COVID-19 stimulated the digitalisation of services, expanding sales channels and diversifying customer engagement.

This research enriches the dynamic capabilities theory by examining how DT&PI influence BM innovation in the FSS, highlighting adaptation to technological trends. It offers a fresh perspective on value creation and stakeholder interaction, contributing to the foundational theory for future FSS BM research.

To augment sales revenue, B2B digital start-ups aim to create and sustain commercial relationships with industry incumbents. However, since these incumbents have traditionally struggled with implementing disruptive digital artifacts, most studies have almost exclusively concentrated on their challenges, leaving the digital start-ups' side underexplored. Therefore, this study seeks to understand how digital start-ups navigate digital implementation (DI) hardships to ultimately achieve digital entrepreneurship success.

An abductive explanatory multi-case study of four industries that pose a variety of implementation challenges for B2B digital start-ups (agriculture, insurance, real estate and construction, and healthcare) was conducted using data collected from 40 interviews with Israeli experts and relevant digital data observations.

This study articulates two main observations. (1) Throughout their journeys, digital start-ups have utilized newly created and/or refined dynamic capabilities (DC) to successfully implement their digital artifacts. Simultaneously, successful DI has enabled digital start-ups to create new DC or sustain and evolve current DC. (2) We provide empirical evidence outlining how digital start-ups using continuous learning have combined causation and effectuation logic throughout their DI journeys.

This study answers a call to explore more explicit digital-related drivers (i.e. DI) for digital entrepreneurship success by studying a highly-ranked country on the Global Entrepreneurship Index (GEI) to achieve this. Moreover, it illustrates how digital start-ups evolve throughout their commercial relationships with industry incumbents, thereby enabling an effective approach for successful DI. Such an approach can be considered very valuable for both practitioners and policymakers. Consequently, it advances digital entrepreneurship as an independent research topic.

This chapter reviews Internet of Things (IoT) as a concept with bibliometric analysis using data selected from the Scopus database. The cited references included two clusters. Also, co-occurrence keyword analysis found four groups. The first cluster shows IoT adoption in agriculture, manufacturing, logistics, and supply chain management. The second cluster includes behavioral models of IoT technology acceptance. The third cluster refers to the adoption of IoT and automation technology in intelligent buildings, smart homes, smart cities, and health care. Finally, the fourth cluster contains information management.

In the era of the digital economy, the digital innovation ecosystem is an important vehicle to alleviate enterprises' resource and capability constraints and thus improve their digital innovation performance. Embedding digital innovation ecosystems for survival and development opportunities has become a new strategic choice for enterprises. However, how digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises has not yet been fully revealed. This study examines whether digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises through ambidextrous capabilities (exploration and exploitation) and the moderating role of strategic flexibility.

A field survey was conducted in China, collecting survey data from 578 complementary enterprises in advanced manufacturing industries embedded in digital innovation ecosystems. This study applies multiple regression analysis to verify the relevant hypotheses.

The results confirmed that (1) digital innovation ecosystem embeddedness has a significant positive effect on complementary enterprises' digital innovation performance; (2) Ambidextrous capabilities play a partial mediating role in the relationship between digital innovation ecosystem embeddedness and complementary enterprises' digital innovation performance. (3) Strategic flexibility positively moderates the effect of digital innovation ecosystem embeddedness on ambidextrous capabilities and digital innovation performance.

The findings, intended to guide enterprises that complement the digital innovation ecosystem to achieve digital innovation and performance improvement, highlight the importance of eco-embedded strategies, ambidextrous capabilities and strategic flexibility.

The finding enriches antecedent research on digital innovation performance and provides practical insights for firms to embed themselves in digital innovation ecosystems to improve performance.