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In effort to understand and reduce flood consequences more effectively and strategically, flood risk assessment has been a cornerstone of a long-term flood management. One component of flood risk assessment is the estimation of a range of possible damage to an area exposed to flooding, that is, the vulnerability curve. The vulnerability curve can be depicted by a stage–damage relationship. This study attempts to investigate how vulnerability to flooding can be quantitatively assessed using a micro-scale approach in Malaysia’s vulnerable areas. A residential area in Kota Bharu was chosen as the case study area. Depth–damage relationships from a multiple regression function of Department of Irrigation and Drainage Malaysia and spatial variability of residential buildings were used for the micro-scale assessment. Final estimates of expected annual damage were then calculated for each building type at 1-, 3- and 5-day flood durations. Results show that the methodology adopted is feasible to be applied for local-scale assessment flood risk assessment in Malaysia. The results also suggest that applying the methodology is possible when given wider availability of resources and information. This is particularly important for a robust end-to-end flood risk assessment for long-term effective flood management in Malaysia.

Based on the service eco-systems perspective, this paper evaluates the strategies and actions adopted by the Government of Pakistan to handle the COVID-19 crisis with the involvement of multiple actors including public, private, third-sector organizations and civil society.

The paper is based on an in-depth analysis of secondary sources including research articles, policy documents, policy briefs, governmental reports, third party evaluations/reports and media publications.

A multi-stakeholder approach was evident during the pandemic with an effort to better manage the crisis which has exerted immense social, cultural, economic and political impacts on the lives of the citizens. Collaborative efforts among stakeholders (government, private and third sector) were witnessed, resulting in a coherent response. The successful management of COVID-19 in Pakistan is attributed to multiple factors including the formation of a specialized public organization which effectively and proactively took data-driven informed decisions and aggregated the efforts of the federal and provincial governments for a timely response.

This paper gives insights for policymakers to create a sustainable post-pandemic socio-economic environment by building resilient structures across the government while promoting cooperation and collaboration. It suggests strategies for policymakers responsible for providing sustainable societal solutions to combat the social, economic and administrative challenges under the pandemic. As Pakistan has managed and contained the pandemic in a relatively efficient way, it is hoped that this paper can provide a learning experience for other countries with similar national contexts.

Globally, prefabrication in housebuilding has evolved as an innovative approach to attain sustainability and affordability. However, the SC, including non-producers and producers, of prefabricated housebuilding projects is still not perceptually aligned, hindering innovation diffusion. This paper investigates the contemporary industry perspective on PHB for conceptualisation, market share and growth, innovation diffusion and the producer's role in the context of New Zealand.

An exploratory qualitative research design was chosen to learn the perceptual stance of the industry. A semi-structured survey was conducted, followed by interviews with selected supply chain participants, who were producers and non-producers and had relevant experience in the PHB industry.

This study reports the common terminologies used by supply chain members, with justification and explanation. Further, the perceived market share and growth of the PHB industry are obtained and compared with subsequent studies to determine the capability and capacity. The perception of the diffusion of PHB by type is reported to portray the overall trend of the industry. In the last, the role of producers as the suppliers of PHB projects is investigated to establish the stakeholder positional criticality.

This study can help researchers and practitioners gain insight into the PHB industry from a multi-dimensional perspective. This study is a potential first step to formalise the policy, programme, strategies and action plan for the uptake of the PHB in the New Zealand.

PHB diffusion in the supply chain perspective, considering multi-dimensional aspects, has not been considered in previous studies as government agencies produce most of the literature. This academic research establishes the theoretical linkage towards PHB diffusion and reports the current status.

This study aimed to examine the efficient market hypothesis (EMH) for the stock markets of 12 member countries of the Organization of Islamic Cooperation (OIC), such as Egypt, Indonesia, Jordan, Kuwait, Malaysia, Morocco, Pakistan, Saudi Arabia, Tunisia, Turkey and the United Arab Emirates (UAE), during the global financial crisis (GFC) and the COVID-19 (CV-19) epidemic. The objective was to classify the effects on individual indices.

The study employed the multifractal detrended fluctuation analysis (MF-DFA) on daily returns. After calculation and analysis, the data were then divided into two significant events: the GFC and the CV-19 pandemic. Additionally, the market deficiency measure (MDM) was utilized to assess and rank market efficiency.

The findings indicate that the average returns series exhibited persistent and non-persistent patterns during the GFC and the CV-19 pandemic, respectively. The study employed MF-DFA to analyze the sequence of normal returns. The results suggest that the average returns series displayed persistent and non-persistent patterns during the GFC and the CV-19 pandemic, respectively. Furthermore, all markets demonstrated efficiency during the two crisis periods, with Turkey and Tunisia exhibiting the highest and deepest levels of efficiency, respectively. The multifractal properties were influenced by long-range correlations and fat-tailed distributions, with the latter being the primary contributor. Moreover, the impact of the fat-tailed distribution on multifractality was found to be more pronounced for indices with lower market efficiency. In conclusion, this study categorizes indices with low market efficiency during both crisis periods, which subsequently affect the distribution of assets among shareholders in the stock markets of OIC member countries.

Multifractal patterns, especially the long memory property observed in stock markets, can assist investors in formulating profitable investment strategies. Additionally, this study will contribute to a better understanding of market trends during similar events should they occur in the future.

This research marks the initial effort to assess the impact of the GFC and the CV19 pandemic on the efficiency of stock markets in OIC countries. This undertaking is of paramount importance due to the potential destabilizing and harmful effects of these events on global financial markets and societal well-being. Furthermore, to the best of the authors’ knowledge, this study represents the first investigation utilizing the MFDFA method to analyze the primary stock markets of OIC countries, encompassing both the GFC and CV19 crises.

There is a continuous drive in automotive sector to shift from conventional lubricants to environmental friendly ones without adversely affecting critical tribological performance parameters. Because of their favorable tribological properties, chemically modified vegetable oils such as palm trimethylolpropane ester (TMP) are one of the potential candidates for the said role. To prove the suitability of TMP for applications involving boundary-lubrication regime such as cam/tappet interface of direct acting valve train system, a logical step forward is to investigate their compatibility with conventional lubricant additives.

In this study, extreme pressure and tribological characteristics of TMP, formulated with glycerol mono-oleate (GMO), molybdenum dithiocarbamate (MoDTC) and zinc dialkyldithiophosphate (ZDDP), has been investigated using four-ball wear tester and valve train test rig. For comparison, additive-free and formulated versions of polyalphaolefin (PAO) were used as reference. Moreover, various surface characterization techniques were deployed to investigate mechanisms responsible for a particular tribological behavior.

In additive-free form, TMP demonstrated better extreme pressure characteristics compared to PAO and lubricant additives which are actually optimized for conventional base-oils such as PAO, are also proved to be compatible with TMP to some extent, especially ZDDP. During cylinder head tests, additive-free TMP proved to be more effective compared to PAO in reducing friction of cam/tappet interface, but opposite behavior was seen when formulated lubricants were used. Therefore, there is a need to synthesize specialized friction modifiers, anti-wear and extreme pressure additives for TMP before using it as engine lubricant base-oil.

In this study, additive-free and formulated versions of bio-lubricant are tested for cam/tappet interface of direct acting valve train system of commercial passenger car diesel engine for the very test time. Another important aspect of this research was comparison of important tribological performance parameters (friction torque, wear, rotational speed of tappet) of TMP-based lubricants with conventional lubricant base oil, that is, PAO and its formulated version.

This research aims to determine the contribution of publications in the context of Türkiye to the international entrepreneurship literature between 2005 and 2022. We examined 471 articles published in international journals in the Web of Science (WoS) Core Collection database using bibliometric analysis techniques. We analyzed the data with the software Biblioshiny+Bibliometrix, SciMAT, and VOSViewer. We used performance, theme and evolution, co-authorship, and document analysis in data analysis. Performance analysis findings show that the most publications were made in 2021, the journal with the most publications was sustainability, and the author with the most publications was Bakır, C. Theme and evolution analysis revealed that the motor themes were corporate entrepreneurship, gender and entrepreneurial intentions in the first period (2005–2014), while institutional entrepreneurship stood out as the niche theme. In the second period (2015–2022), “corporate entrepreneurship” and “performance” emerged as the motor themes, while the niche themes in this period were “Syrian refugees” and “entrepreneurial intentions.” Document analysis findings show that the most studied entrepreneurship types are gender, family, corporate, social, and small business, respectively. In addition, immigrant/refugee entrepreneurship is emerging as a new topic, while indigenous entrepreneurship, informal entrepreneurship, sustainable entrepreneurship, and religion entrepreneurship are the most minor studied topics in entrepreneurship. Evidence-based decision-making inputs were obtained for those holding the resource allocation authority in Türkiye. Policymakers and funders, as well as individuals and institutions that want to design the future in terms of resources, can benefit from the findings and analysis of this chapter. Türkiye, which ranks 26th in the world regarding entrepreneurship, must develop a policy based on data.

The aim of this chapter is to contribute toward the phenomena of women entrepreneurship from an emerging economy perspective through a dynamic capability's perspective. The challenges faced by women entrepreneurs in a nonsupportive entrepreneurial ecosystem reshaped by digitization will contribute to the burgeoning women entrepreneurship literature. In order to survive in a challenging entrepreneurial ecosystem, women entrepreneurs need dynamic capabilities to face the challenges of a modern digital world. This chapter problematizes the challenges of the digital world and its role in modern day businesses.

This research investigates the mediation effect of perceived organizational support on the relationship between organization-based self-esteem and perceived occupational stress of teachers.

The present quantitative venture follows a causal research design to unveil the relationship among organization based self-esteem (independent variable), perceived occupational stress (dependent variable) and perceived organizational support (intervening variable). The research surveys 813 educators from nineteen selected distinct areas of Dhaka city; the survey instrument has twenty-six items apart from some general inquires about the respondents. To address the dynamic interplay among these variables, a confirmatory factor analysis (CFA) is conducted within a structural equation modeling (SEM) framework.

Teachers with low self-esteem perceived a high level of occupational stress, whereas teachers who perceived high organizational support feel low occupational stress. Increasing organizational support not only increases organization-based self-esteem but also mediates the relationship between self-esteem and occupational stress.

Teachers' stress is not only an increasing problem over the years but also it was one of the top six most stressful professions. The present study outlines the possible organizational initiatives that can reduce the stresses of the teaching profession.

The findings of the present study square with several theoretical frameworks such as the job demands–resources (JD–R) model and conservation of resources (COR) theory. The results highlight the fact that allowing school teachers to express their ideas and points of view makes them feel esteemed. Likewise, good relations with the school head and getting positive feedback are found to be contributing factors. The teachers feel lesson planning overburdensome and undue office inspections hurt their self-esteem. Any school can increase the self-esteem of the teachers by providing support and training to adjust to changes.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.