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This paper addresses the challenges associated with forecasting electricity consumption using limited data without making prior assumptions on normality. The study aims to enhance the predictive performance of grey models by proposing a novel grey multivariate convolution model incorporating residual modification and residual genetic programming sign estimation.

The research begins by constructing a novel grey multivariate convolution model and demonstrates the utilization of genetic programming to enhance prediction accuracy by exploiting the signs of forecast residuals. Various statistical criteria are employed to assess the predictive performance of the proposed model. The validation process involves applying the model to real datasets spanning from 2001 to 2019 for forecasting annual electricity consumption in Cameroon.

The novel hybrid model outperforms both grey and non-grey models in forecasting annual electricity consumption. The model's performance is evaluated using MAE, MSD, RMSE, and R², yielding values of 0.014, 101.01, 10.05, and 99% respectively. Results from validation cases and real-world scenarios demonstrate the feasibility and effectiveness of the proposed model. The combination of genetic programming and grey convolution model offers a significant improvement over competing models. Notably, the dynamic adaptability of genetic programming enhances the model's accuracy by mimicking expert systems' knowledge and decision-making, allowing for the identification of subtle changes in electricity demand patterns.

This paper introduces a novel grey multivariate convolution model that incorporates residual modification and genetic programming sign estimation. The application of genetic programming to enhance prediction accuracy by leveraging forecast residuals represents a unique approach. The study showcases the superiority of the proposed model over existing grey and non-grey models, emphasizing its adaptability and expert-like ability to learn and refine forecasting rules dynamically. The potential extension of the model to other forecasting fields is also highlighted, indicating its versatility and applicability beyond electricity consumption prediction in Cameroon.

The purpose of this article is to assess the extent to which environmental economic practices are recognized and implemented in developing countries, with a specific emphasis on the Nigerian construction sector.

To examine the extent of awareness and usage, a quantitative research approach was adopted with close-ended questionnaires disseminated to construction professionals in Nigeria. The collected data were subjected to analysis using various statistical techniques such as percentages, frequencies and mean scores. Furthermore, to investigate any significant differences in the respondents' opinions, the Kruskal–Wallis H-test was applied.

The study's findings indicate that the level of awareness and implementation of environmental economic practices among construction professionals in Nigeria is limited. Based on the findings of this study, a roadmap of recommendations has been proposed to promote the adoption of environmental economic practices in the Nigerian construction industry. The implementation of these recommendations can help reduce the negative impact of construction activities on the environment and public health and contribute to the development of sustainable cities, communities and societies.

The outcomes from this study can inform policy and decision-making by providing insights into the level of knowledge and awareness of environmental economic practices among construction professionals in Nigeria.

The findings from this study provide a baseline for assessing the level of knowledge and awareness of sustainable practices among construction professionals in Nigeria, which can inform future studies on the effectiveness of training and awareness programs.

This study aims to develop an overall project success (OPS) model by investigating the mediation impact of value management (VM) implementation between VM critical success factors (CSFs) and OPS as well as the moderation impact of VM CSFs between VM implementation and OPS.

In total, 335 structured questionnaires were administered to relevant stakeholders in the study area. The research used a partial least square structural equation modeling (PLS-SEM) to model the relationship among VM implementation, CSFs and OPS.

The results revealed that there is an indirect positive and significant correlation among the variables. The model prediction analysis also significantly impacted with 59.9% on OPS by setting VM implementation as a mediator variable and 61% by setting VM CSFs as a moderation variable.

This research work will serve as a guide or benchmark for decision-makers who want to use VM to improve the success of their building projects.

This study fills the knowledge gap by identifying and emphasizing the impact of VM CSFs and activities on OPS.

This research paper aims to investigate reinforced concrete (RC) walls' behaviour under fire and identify the thermal and mechanical factors that affect their performance.

A three-dimensional (3D) finite element (FE) model is developed to predict the response of RC walls under fire and is validated through experimental tests on RC wall specimens subjected to fire conditions. The numerical model incorporates temperature-dependent properties of the constituent materials. Moreover, the validated model was used in a parametric study to inspect the effect of the fire scenario, reinforcement concrete cover, reinforcement ratio and configuration, and wall thickness on the thermal and structural behaviour of the walls subjected to fire.

The developed 3D FE model successfully predicted the response of experimentally tested RC walls under fire conditions. Results showed that the fire resistance of the walls was highly compromised under hydrocarbon fire. In addition, the minimum wall thickness specified by EC2 may not be sufficient to achieve the desired fire resistance under considered fire scenarios.

There is limited research on the performance of RC walls exposed to fire scenarios. The study contributed to the current state-of-the-art research on the behaviour of RC walls of different concrete types exposed to fire loading, and it also identified the factors affecting the fire resistance of RC walls. This guides the consideration and optimisation of design parameters to improve RC walls performance in the event of a fire.

This study aims to fill data gaps concerning solutions and practices used in sustainable food systems (SFS) in higher education (HE). The development of SFS is a vital global challenge in which HE may play a significant role.

Literature search and content analysis of found papers were performed. Additionally, the quantitative time trend of the emergence of research connected to SFS HE and the connectivity of content within the research papers about research questions were determined by regression analysis and data visualization, respectively.

It is evident that SFS education in universities (higher education institutes) is emerging, and the number of research papers is rapidly increasing. In the reviewed papers, universities recognized their significant role in managing wicked problems. The motivation for developing SFS education was high, with strong ambitions. SFS in HE includes developing education in-house through trans- and multidisciplinary solutions, developing education with stakeholders and supporting student growth to become responsible professionals and citizens.

When developing SFS education in HE both practical and theoretical research is needed. Ethical dimensions should be included in both research orientations because of the moral complexity that exists in SFS issues.

This study shows that competence in trans- and multidisciplinary working is needed. Concomitantly, the ability of cooperation between HE, business and society is vital when solving global food challenges. Also, the local tradition of food cultivation should be respected and maintained.

To the best of the authors’ knowledge, this is the first review on the development of SFS education in HEIs. A qualitative content analysis and data visualization were used to enrich the review.

The main objective of this paper is to analyze how leadership unity (LU) within universities affects the innovativeness of faculty, with a focus on the potential moderating role of strategic sensitivity (SS).

The conceptual model of this research shows that SS and LU of the university impact the faculty's innovativeness. Meantime, the moderating effect of SS is assessed. A 49-item questionnaire was administered to 350 respondents who were managers and faculties of the university. The hierarchical regression technique was used for analyzing data and testing hypotheses.

The findings support both a curvilinear relationship based on a concave upward pattern and a linear relationship between LU in the university and the innovativeness of faculty. In addition, the university's SS positively influences the faculty's innovativeness. SS negatively moderates the curvilinear relationship between LU and faculty's innovativeness, i.e. the U-shaped effect exists only when the level of SS is high.

The results of this study shed new light on the relationships between LU and SS with innovativeness in the higher education landscape. It underlines the importance of SS as a moderator in the relationship between LU and innovativeness. This study was conducted in a developing country under sanctions with an Eastern culture, Iran. Thus, it is recommended that the conceptual framework of this study be tested in different countries with cultural diversity to generalize its findings.

Administrators of universities need to recognize that creating unity and cohesion among managers of various levels of the university is crucial. They should also be aware that responses to external changes can lead to new opportunities for the university. Embracing transformation within the organizational strategies of the university will have a significant influence on competition, politics, and internal operations.

This research contributes to the academic discussions on the importance of LU and SS and also the moderation effect of SS in driving and promoting innovativeness in among faculties by providing empirical evidence. The results present valuable insights for scholars, practitioners and policymakers seeking to understand innovativeness among faculties in the higher education setting.

This study aims to provide insights into the possible impact of International Public Sector Accounting Standards (IPSAS) on public governance and perceived levels of corruption in developing countries.

Through a multivariate analysis on panel data applied to 36 countries in the Middle East and North Africa (MENA) region and sub-Saharan Africa over the period 2010–2020, the authors test the impact of IPSAS adoption on transparency, accountability and perceptions of less corruption. The authors examine the moderating role of transparency and accountability in the strength of the relationship between IPSAS and perceived corruption.

The main results show that IPSAS adoption promotes an increase in transparency and accountability and leads to the perception of less corruption. Additional tests show that transparency and accountability strengthen the effect of IPSAS adoption and experience on perceived corruption.

The first limitation may be the use of the Transparency International CPI to measure the level of perceived corruption. Probably, the CPI does not reflect the actual levels of corruption in countries while the literature argues that these two measures are related. Also, the lack of data on the status and level of adoption of IPSAS by governments may be one limitation of the sample.

The study may help public authorities in their decision to adopt IPSAS. In light of the findings, standard-setting bodies could be encouraged to strengthen the disclosure requirements of IPSAS that make governments more transparent and accountable to limit perceptions of corruption.

This study may also help citizens understand the benefits of such reforms in protecting public assets and how such standards may help improve social welfare.

To the best of the authors’ knowledge, this is one of the few studies that examines the impact of IPSAS on good governance by combining the dimensions of transparency, accountability and perceptions of corruption in DCs. It also provides insights into the moderating role of public governance pillars. Finally, it includes the IPSAS experience of the country, which has been little tested previously.

This paper aims to present a numerical investigation into heat transfer and entropy generation resulting from magnetohydrodynamic laminar flow through a microchannel under asymmetric boundary conditions. Furthermore, the authors consider the effects of viscous dissipation and Joule heating.

The finite difference method is used to obtain the numerical solution. Simulations are conducted across a broad range of Hartmann (Ha = 0 ∼ 40) and Brinkman (Br = 0.01 ∼ 1) numbers, along with various asymmetric isothermal boundaries characterized by a heating ratio denoted as ϕ.

The findings indicate a significant increase in the Nusselt number with increasing Hartmann number, regardless of whether Br equals zero or not. In addition, it is demonstrated that temperature differences between the microchannel walls can lead to substantial distortions in fluid temperature distribution and heat transfer. The results reveal that the maximum entropy generation occurs at the highest values of Ha and η (a dimensionless parameter emerging from the formulation) obtained for ϕ = −1. Moreover, it is observed that local entropy generation rates are highest near the channel wall at the entrance region.

The study provides valuable insights into the complex interactions between magnetic fields, viscous dissipation and Joule heating in microchannel flows, particularly under asymmetric heating conditions. This contributes to a better understanding of heat transfer and entropy generation in advanced microfluidic systems, which is essential for optimizing their design and performance.