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The purpose of this paper is to use Delphi technique to assess the applicability of coupling various project delivery methods (PDMs) and contract strategies (CSs) for delivery of public building projects (PBP) in Ethiopia.

To achieve the objective of this research, an online Delphi study was designed, conducted and analyzed using various statistical procedures. Results were compared to CII’s project delivery and CS (PDCS) tool, a US-based PDM selection tool.

This study converged in the third round signifying a consensus on the importance of design–build and construction manager at risk as alternatives to design–bid–build. In addition, “controlling schedule growth” was deemed to be a major performance measure that needs to be considered for PBP in Ethiopia, a result consistent with the outcomes from CII’s PDCS tool.

Among existing studies, none to the best of the authors’ knowledge has focused on a holistic approach to identify the most appropriate pairings of PDMs and CSs for PBP which was critically needed due to the magnitude and high stakes of these projects. This research is a steppingstone toward gaining knowledge on how to approach these types of projects in fast-growing environments thirsty for new building projects such as in Ethiopia.

The purpose of this study is to consider the dynamics of Casson–Walters-B alongside gyrotactic microorganisms through the investigation of antibacterial and antiviral mechanisms using silver nanoparticles (AgNPs). The Casson fluid and Walters-B flow from the penetrable plate to the boundary layer (BL) in this analysis. The antiviral and antibacterial mechanisms of AgNPs were separately examined in this study.

The physical phenomenon of this problem was analyzed with partial differential equations (PDEs). These PDEs were changed into ordinary differential equations (ODEs) to further explain the significance of pertinent control parameters. The set of equations is solved numerically by implementing the spectral relaxation method (SRM). SRM is a numerical technique that uses the basic techniques of Gauss-Seidel. The SRM first decouples and linearizes the coupled nonlinear set of ODEs.

In this finding, it is found that the thermal radiation parameter produces higher temperatures within the BL to cause blockage in viral replications. It is found in this study that the magnetic parameter assisted in disinfection by lowering the antiviral and antibacterial mechanisms within the momentum BL. This is evident from the reduction in the velocity and momentum BL as the Casson and Walters-B parameters increase.

This paper is unique because it examined the antiviral and antibacterial mechanisms by using AgNPs. Prior to the authors’ understanding, no study of this type was conducted in the past. To the best of the authors’ knowledge, no other study in the past has examined the mechanisms of antiviral and antibacterial separately within the BL. Also, the simultaneous flow of Casson (honey) and Walters-B fluids were considered flowing through the vertical porous plate to the BL.

The delay in real estate projects in India is pervasive. Organization and management (O&M) and project management (PM)-related challenges are argued to contribute to project delays. This study examined the O&M and PM factors that cause delays, the level of implementation of various O&M and PM aspects in real estate projects and how the challenges can be alleviated.

Perception surveys among the consumers and relevant stakeholders engaged in real estate projects in the Bhubaneswar and Cuttack regions of India were conducted to collect data on the factors of delay and implementation of the O&M and PM aspects. Relevant statistical methods and structural equation modeling (SEM) were used for data analysis.

Findings suggest that from the O&M point of view, poor decision-making, mishandling of finance, concurrent execution of many projects, diversion and misuse of finance for unrelated activities, lack of PM personnel and poor management contribute to the delay. Further, although the project initiation is satisfactorily done, most of the PM principles are not largely used, thus leading to delay.

The study does have limitations, including its reliance on a perception survey of consumers and stakeholders, a limited sample size and a restricted number of projects. Nevertheless, the study highlights the need to address poor O&M and the insufficient application of PM principles to combat project delays in the Indian real estate sector.

Proper O&M and adequate application of PM will enable professional management of the projects and avoid delay.

Proper O&M and the application of adequate PM would reduce delays in real estate projects. Consequently, conflicts between the companies and consumers might be reduced and housing and infrastructure demands might be met.

The study manifested that the lack of adequate implementation of O&M and PM aspects leads to delays. So, it is theorized that O&M and PM play critical roles in the success of real estate projects. Appropriate implementation of the principles and best practices linked to these aspects might alleviate the challenges of delay in real estate projects in India.

This study aims to present a model for detecting and predicting creative accounting in companies listed on the Tehran Stock Exchange (TSE).

The authors conduct this research in three stages. First, the authors review the literature to determine the dimensions, components, indicators and techniques of creative accounting. Second, the authors conduct semi-structured interviews with experts using the fuzzy Delphi technique to obtain screening and reach a consensus. Finally, the authors develop a model to predict creative accounting by classifying the financial statements of the sample companies into two groups based on the use or non-use of creative accounting techniques, measuring the indicators determined in the previous stage, running various machine learning algorithms and choosing the superior algorithm.

The results indicate the usefulness of accounting information for detecting and predicting creative accounting and the relevance of several financial attributes as important predictors. The results also indicate the superiority of extremely randomized trees over other algorithms in predicting creative accounting and suggest that the primary purpose of creative accounting in Iran is earnings management. Contrary to the political cost hypothesis, large Iranian companies use creative accounting to inflate profits.

The present research also has several limitations that must be considered, and caution must be exercised in interpreting and generalizing the findings as specified in the revised manuscript.

This study’s implications are significant for policymakers, standard-setters and practitioners. By recognizing the detrimental effects of creative accounting on financial transparency within companies, policymakers can address existing gaps in accounting standards to minimize the potential for earnings manipulation. Consequently, strengthening internal and external mechanisms related to a firm’s financial performance becomes achievable. The study provides evidence of the need for audit firms to recognize the importance of creative accounting and consider creative accounting in their audit plans to prevent insufficient or even misleading disclosure by companies that extensively use creative accounting practices in their financial reporting. Moreover, knowledge of creative accounting techniques can help auditors assess audit and detection risks and serve as a valuable guide for reducing audit costs and improving audit quality.

Given that creative accounting practices distort the true or real accounting results, curbing creative accounting practices reduces corporate failures and could lead to the reduction of job losses and other social consequences.

This study uses a unique database in Iran to determine a model for predicting creative accounting using a mixed-method methodology, qualitative and quantitative, to identify creative accounting techniques and run various machine learning algorithms.

Most construction projects are undertaken with the incentive of some form of profit which in business attracts disputes that key disputing parties intend to resolve through mechanisms such as arbitration as early as possible so that they may advance with other activities associated with the project. However, this intention is regularly unfulfilled, disappointing the parties with late arbitration resolution. This study, therefore, explored the duration influencing factors (DIFs) facing arbitration practice in the Tanzania construction industry.

A concurrent convergence mixed methods approach was used where a total of 12 DIFs were identified from the literature, and data were then collected from 39 construction arbitrators, 8 semi-structured interviews and 4 documentary reviews. Descriptive and inferential statistics were employed for quantitative data and directed content analysis for the qualitative data.

Results show that contrary to most people’s convictions, delays in arbitration are regularly caused by the disputing parties rather than the arbitrating party or the authority. The study identified cooperation amongst the tribunal parties, poor accuracy and submission of documents and material evidences, late payment of arbitration fees, and skills, experience, reputation and profession of the arbitrator to be the most critical factors that cause late arbitration resolution.

The use of mixed methods concurrent triangulation convergence approach provides a unique contribution to knowledge by highlighting how the efficacy of arbitration in time performance could be further developed through understanding the critical factors that drive the proceedings duration in the Tanzania construction industry.

This study aims to investigate the asymmetric impact of the COVID-19 pandemic on the stock market returns of companies listed on the Casablanca Stock Exchange.

To achieve this objective, we utilized the SymCovid series, which comprises two sub-series: one representing the deterioration of the pandemic situation (NEG) and the other representing the improvement of the pandemic situation (POS). We employed the Nonlinear Autoregressive Distributed Lag model, incorporating Bounds Testing as proposed by Pesaran and Shin (1999) and Pesaran et al. (2001), to explore the asymmetry of the pandemic’s impact on stock prices listed on the Casablanca stock exchange.

Our analysis using the NARDL econometric model reveals an asymmetric effect of COVID-19 on stock prices. Notably, we observe that stock prices react more strongly to a worsening pandemic situation than to an improvement, on average. Furthermore, our main findings indicate that while the improvement in the pandemic situation has no significant long-term impact on stock prices, it does exhibit a significant positive effect in the short term. Conversely, the deterioration in the pandemic situation has a more pronounced negative effect on stock prices in the long term than the short term.

Our study fills a gap in the existing literature by focusing on the impact of the COVID-19 pandemic on stock returns in the context of the Casablanca Stock Exchange, which has been relatively understudied compared to other regions such as Asia, Europe and the Americas. We go beyond previous research by examining whether stock returns exhibit asymmetric responses to changes in the pandemic situation, highlighting potentially unique dynamics in emerging market economies during crises and providing valuable information for investors, policymakers and researchers.

This paper aims to examine the dynamic relationship between economic growth and sustainable development, integrating the Environmental Kuznets Curve (EKC) in 22 Organization of Islamic Cooperation (OIC) member countries across income groups.

Using annual data between 1990 and 2022, the authors apply the cross-correlation coefficient (CCC) approach of Narayan et al. (Economic Modeling, 2016, 53, 388–397) to examine the lead/lag relationship between GDP per capita and sustainable development. This study further validates the findings through a panel Granger causality test and a fixed panel regression model.

This research provides evidence of a U-shaped EKC for only 1 out of 22 (5%) OIC countries. For 13 out of the 22 (59%) OIC countries, increasing income growth is expected to enhance sustainable development in the future. The results show that as income levels rise, there will be a more significant decline in sustainable development for high-income OIC countries in the future than for both middle-income groups, contradicting the EKC hypothesis. The findings from the panel Granger causality and panel regression models also support the CCC results.

This study proposes a reverse version of the EKC hypothesis and contributes to the literature on economic growth and environmental sustainability. With increasing economic growth, the results can assist OIC member governments and policy-makers in designing tailored policies and practical measures for future sustainable development.

Women make a major contribution to the agricultural sector, especially in developing countries. Despite this, women still face many obstacles in carrying out their agricultural activities. These obstacles have a negative impact on their productivity and create a gender gap. This paper analyses the difference in agricultural productivity between male-headed and female-headed households in Burkina Faso.

Using data from the Permanent Agricultural Survey (EPA), we applied the Blinder-Oaxaca decomposition method to determine the size of the gender gap and identify the variables explaining this gap. In this study, we used the value of production per farm worker as a measure of productivity.

The results indicate a gender gap of 43.8 percentage points in favor of male-headed households. Around 131% of this difference is explained by differences in observable household characteristics. The factor that most explains this difference in productivity is the difference in the total area of land available to households.

This finding calls for women’s access to land to be considered in the design and implementation of agricultural development policies.

One of the main contributions of this article in relation to previous studies lies in the unit of analysis. Rather than focusing on individual producers, as in previous studies, we have instead considered the household as the unit of analysis, since in developing countries such as Burkina Faso, production decisions are taken at household level. It contributes to inform economic policy decisions by providing decision-makers with the factors on which they can act to bring about an increase in agricultural productivity by reducing the gap between male-headed households and female-headed households.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0923

This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN).

A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME.

Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME.

The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively.

This study examines the impact of firm-specific and macroeconomic factors on the working capital behavior of firms listed in the Middle East and North African (MENA) region.

This study is based on a panel data analysis of 687 firms listed on 11 MENA markets, carried out using the Generalized Method of Moments (GMM) approach.

The results of this study reveal that profitable firms with high levels of operating cash flows adopt a conservative working capital management. Young firms with rapid growth rates, highly leveraged firms and firms with large investments in fixed assets have higher liquidity needs, which explains their tendency to pursue aggressive working capital strategies. Similarly, large firms exercise their bargaining power over their clients and suppliers to implement an aggressive approach of working capital management. Finally, firms do not have the luxury to decide how working capital should be managed when they are subject to outside macroeconomic forces that affect their stakeholders as well.

The findings of this study can help managers adopt efficient practices and identify optimal working capital levels. Firms in the MENA region maintain excess reserves of cash, which causes under-investment and inefficient allocation of resources in the economy. Improving working capital management practices can allow firms to regain operational efficiency, enhance financial performance and support economic growth.

To the best of the authors' knowledge, this study investigates this topic in MENA emerging markets and contributes to enriching the existing corporate finance literature in emerging markets.