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The purpose of this paper is to establish a two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem with three-parameter interval grey number to evaluation of agricultural drought resistance grade of 18 cities in Henan Province.

The clustering process is divided into two stages. In the first stage: Combining variance and time degree, the time weight optimization model is established. Applying the prospect theory, the index weight optimization model is established. Then, with the help of grey possibility function, the first stage of grey cloud clustering evaluation is carried out. In the second stage: the weight vector group of kernel clustering is constructed, and the grey class of the object is determined. A two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem is proposed.

This paper indicates that 18 cities in Henan Province are divided into four categories. The drought capacity in Henan province is high in the east and low in the west, high in the south and low in the north and the central region is relatively stable. The drought is greatly affected by natural factors. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical method for drought resistance assessment, and provides theoretical support for farmers to grasp the drought information timely and improve the drought resistance ability.

The model in this paper solves the situation of ambiguity and randomness to some extent with the help of grey cloud possibility function. Moreover, the time weight of time degree and variance are used to reduce the volatility and the degree of subjective empowerment. Considering the risk attitude of the decision makers, the prospect theory is applied to make the index weight more objective. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

A learning-focused culture promotes creativity, innovativeness and the acquisition of novel insights and competencies. The study aims to explore the relationship between human resource development (HRD) practice and employee competencies using organizational learning culture as a mediating variable.

Data were collected from 828 employees of 37 health care institutions comprising 24 (internationally-owned) and 13 (indigenously-owned). Construct reliability and validity was established through a confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

Data supported the hypothesized relationships. The results show that training and development and employee competencies were significantly related. Career development and employee competencies were significantly related. Organizational learning culture mediates the relationship between training and development and employee competencies. However, organizational learning culture did not mediate the relationship between career development and employee competencies.

The generalizability of the findings will be constrained due to the research’s health care focus and cross-sectional data.

The study’s findings will serve as valuable pointers to policy makers and stakeholders of health care institutions in developing system-level capacities that promote continuous learning and adaptive learning cultures to ensure sustainability and competitive advantage.

By evidencing empirically that organizational learning culture mediates the relationship between HRD practices and employee competencies the study extends the literature.

The present study examines the relationship between personality traits (PTs) and conflict management styles (CMSs) directly and indirectly through leadership effectiveness (LE) in Pakistan.

This quantitative study employs a survey questionnaire to collect cross-sectional data from academic leaders of higher education institutes (HEIs) in Pakistan. The authors utilized 325 useable cases to conclude the results.

The findings through the structural equation model (SEM) resulted in a positive and significant effect of agreeableness (AGS) on integrating (ITG), avoiding (AVG), obliging (OBG), compromising (COG) and dominating (DOG) styles. Extraversion (EXN) positively and significantly affects ITG, OBG, DOG and COG. Emotional stability (EMSY) is a positive and significant predictor of ITG, AVG, OBG and COG. The conscientiousness (CNS) trait significantly and positively predicts ITG, OBG, DOG, COG and AVG. Likewise, openness (OPS) positively and significantly affects ITG, OBG, DOG and COG styles. On the other hand, EXN and OPS negatively and insignificantly affect AVG. Finally, EMSY is the negative and insignificant predictor of DOG among academic leaders.

This study offers additional insights into understanding direct and indirect connections between PTs and CMSs through EL. It would support the development of effective policies and organizational setup to resolve and manage conflict and employees' behaviour. Finally, the findings would further enrich the worth of literature through another empirical confirmation.

This study offers the original contribution of PTs and CMSs among academic leaders in HEIs of Pakistan.

The purpose of this paper is to investigate the effect of an admixture, Swine-waste Bio-char (SB), on the water absorption characteristics of cement pastes.

The effect of SB percentages, heat treatment temperatures, water/binder ratios, and age on the water absorption percentages (WAPs) of SB modified cement pastes were investigated using scanning electron microscopy-energy dispersive spectra, FTIR, Brunauer-Emmett-Teller, and laboratory experiments.

The WAPs of cement pastes with SBs produced at the low treatment temperature (LTT) of 340°C and 400°C were significantly lower (p<0.01) than pastes with SBs produced at the high treatment temperature (HTT) of 600°C and 800°C. This was attributed primarily to the more dominant presence of hydrophobic alkyl surface groups from non-volatilized matter in LTT-SBs. This had also resulted in lower surface areas and pore volumes in LTT-SBs. As a result of the volatilization of these labile hydrophobic groups at HTT, HTT-SBs were more hydrophilic and had higher surface areas and pore volumes. Consequently, HTT-SB pastes had higher WAPs and no significant differences (p<0.05) existed between HTT-SB pastes and control pastes. Also, low water/binder ratios and aging reduced water absorption of SB modified cement pastes.

LTT-SBs reduce water absorption and could reduce concrete deterioration; and as such, associated building repair, maintenance, and adaptation costs. Notably, reductions in concrete water absorption will extend the service life of concrete buildings and infrastructures, particularly in unfavorable environmental conditions. The observed benefits are tempered by the current lack of information on the effects of SB on compression strength, workability, and other durability properties.

SB utilization in concrete buildings will enhance swine-waste disposal and reduce negative environmental impacts on swine farming communities; consequently, improving their quality of life.

Current bio-char research is focused on plant-derived bio-char toward soil remediation and contaminant removal, with very limited applications in concrete. This research advances knowledge for developing livestock-derived bio-char, as a PCRM, toward more sustainable and durable concrete structures.

This study aims to illustrate how collaborative platforms may leverage active community for climate change adaptation to implement biodiversity preservation policies.

This study adopts the Dynamic Performance Governance methodological framework to analyze the causal relationships affecting biodiversity preservation policy outcomes.

Active community reduces harmful factors for biodiversity (i.e. biological threats and anthropogenic pressure), limiting the risk of extinction of perennial plants. Stakeholders’ prior knowledge is an enabling condition of climate adaptation processes as it triggers the adoption of prescriptions and cultural changes in a community.

The study provides methodological guidance to define measures to deliver material information to support environmental performance governance. It elaborates an inventory of short- and long-term performance indicators integrating natural-science targets into accounting measures that can support policymakers operating in other contexts to implement climate change adaptation policies.

As a response to the study findings, social implications provide insights into how active community in collaborative platforms for climate change may support stakeholders to address natural resources imbalances, define strategies to share the burden among them and intervene on multiple policy domains (e.g. financial, environmental and social).

Climate change adaptation challenges are conceptualized as “super wicked problems,” and the collaborative platforms designed to address them are rendered as complex adaptive systems. This makes the paper go beyond traditional environmental governance, demonstrating that stakeholders’ interactions within collaborative platforms harness active community specialized knowledge.

The application of steel fiber reinforced concrete (SFRC) beams is limited in practice, partially due to the lack of accurate shear strength prediction models. This study aims to develop a reliable shear strength prediction model for SFRC beams.

In this study, an artificial neural network was employed to predict the shear strength of SFRC beams, utilizing a comprehensive database of 562 experimental studies. Multiple neural networks were established with varying hyperparameters, and their performance was evaluated using statistical parameters.

The neural network with 11 neurons showed superior results than other networks. The performance evaluation, efficiency and accuracy of the selected neural network were examined using margin of deviation, k-fold cross-validation, Shapley analysis, sensitivity analysis and parametric analysis. The proposed artificial neural network model accurately predicts the shear strength and outperforms other existing equations.

This research contributes to overcoming the limitations of existing prediction models for shear strength of SFRC beams without stirrups by developing a highly accurate model based on ANN. Utilizing a comprehensive database and rigorous evaluation techniques enhances the reliability and applicability of the proposed model in practical engineering applications.

Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap.

The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers.

Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others.

The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry.

The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.

This paper draws on the affordance perspective, to explore the social media (SM) usage experiences that might render valuable for academic women professionals, for knowledge exchange, networking and success. Owing to the increased SM usage during COVID-19 pandemic, this paper tries to find out that in what ways do SM affordances facilitate the underprivileged group of women professionals to grow in their careers in a masculine, conservative society through knowledge exchange.

By utilizing qualitative study design, the authors collected data from 31 women employed in Pakistani universities, through unstructured questionnaires. The responses were analyzed through Nvivo.

The generated themes suggested that women in Pakistan are aware of SM's potential for knowledge exchange among fellow professionals. They use it to aid them in communication, collaboration and networking. Additionally, they utilize it to share knowledge and build networks that are vital for career progression and success.

The paper concludes with the implications for practitioners that would aid them in boosting career prospects for women academicians through SM usage in a developing country Pakistan; where women's career outlooks are not as promising as for men; or as bright as for women working in the developed economies.

This a unique attempt to explore knowledge exchange dimensions with the help of SM in the context of working women by the deploying the phenomenological approach.