Search results

This paper aims to investigate the impact of governance quality on total unemployment in general and female unemployment in particular in the Middle East and North Africa (MENA) region, comparing the post-Arab Spring period to the pre-Arab Spring era.

A fixed-effects model was used to analyze data from 15 MENA countries from 2002 to 2019.

Our results generally indicate that following the Arab Spring, an enhancement in governance quality is linked with a reduction in unemployment in the MENA region, specifically in the Levant and GCC regions, with this reducing effect being stronger for female unemployment compared to total unemployment. Yet, this trend does not hold in North Africa, where government improvements do not result in better employment.

This study uniquely uncovers the different effects of governance quality on unemployment across sub-regions and sheds light on its significant implications on female unemployment. The findings offer valuable insights for policymakers interested in the relationship between governance quality and economic outcomes in the region.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0826

Low-carbon concrete represents a new direction in mitigating the global warming effects caused by clinker manufacturing. Utilizing Saudi agro-industrial by-products as an alternative to cement is a key support in reducing clinker production and promoting innovation in infrastructure and circular economy concepts, toward decarbonization in the construction industry. The use of fly ash (FA) as a cement alternative has been researched and proven effective in enhancing the durability of FA-based concrete, especially at lower replacement levels. However, at higher replacement levels, a noticeable impediment in mechanical strength indicators limits the use of this material.

In this study, low-carbon concrete mixes were designed by replacing 50% of the cement with FA. Varying ratios of nano-sized glass powder (4 and 6% of cement weight) were used as nanomaterial additives to enhance the mechanical properties and durability of the designed concrete. In addition, a 10% of the mixing water was replaced with EMs dosage.

The results obtained showed a significant positive impact on resistance and durability properties when replacing 10% of the mixing water with effective microorganisms (EMs) broth and incorporating nanomaterial additives. The optimal mix ratios were those designed with 10% EMs and 4–6% nano-sized glass powder additives. However, it can be concluded that advancements in eco-friendly concrete additive technologies have made significant contributions to the development of sophisticated concrete varieties.

This study focused at developing nanomaterial additives from Saudi industrial wastes and at presenting a cost-effective and feasible solution for enhancing the properties of FA-based concrete. It has also been found that the inclusion of EMs contributes effectively to enhancing the concrete's resistance properties.

This study aims to enhance the resilience of foamed concrete (FC) against carbonation and water absorption (WA) by integrating microorganisms, specifically Aspergillus iizukae EAN605.

The focus was on understanding how variables such as microorganism concentration, concrete density and water-to-cement (w/c) ratio affect these properties. Optimal results were observed under specific conditions—FC density set at 1800 kg/m³, a w/c ratio of 0.5 and an Aspergillus iizukae EAN605 concentration of 0.5 g/L—resulting in significant reductions in carbonation and WA compared to standard FC.

It is observed that fungi not only fill pores with calcium oxalate but also limit carbonation by consuming CO₂ and block water penetration through their mycelial network. A central composite design within response surface methodology was employed for the experimental design, resulting in mathematical models that align closely with the empirical data. The models identified the most effective parameters for minimizing carbonation depth: FC density at 1970 kg/m³, fungal concentration at 0.585 g/L and w/c ratio at 0.470. Further regression analysis showed a high correlation between the experimental data and the predicted outcomes, with a coefficient of determination (R²) of 92.29 and a model F-value of 16.45.

Statistical analysis highlighted the significant roles of density and fungal concentration in these reductions. Besides, scanning electron microscopy provided visual evidence of fungal-mediated mineral formation in FC, supporting the empirical findings. Overall, the study demonstrated the effective use of Aspergillus iizukae EAN605 in enhancing the durability of FC, marking an innovative stride in sustainable construction materials.

When encountering novel technology, customers often use the term “cool” to express their thoughts; therefore, coolness has become crucial for launching service robots. However, research on the impact mechanism of “coolness” is lacking. This study explored the relationship between delight and behavioral intention regarding the coolness of service robots in the food and beverage industry while discussing the mediating roles of utilitarian and hedonic values.

Questionnaires were distributed online with links to the survey posted on restaurant discussion boards on Facebook and online community platforms such as Dcard. In total, 540 responses were deemed valid. The hypotheses were tested using the partial least squares structural equation modeling method.

The results indicate that coolness positively impacted both utilitarian and hedonic values and that both perceived values positively impacted delight. Moreover, coolness does not directly impact delight but must be mediated by perceived value to be effective.

Increasing customer perceptions of the coolness of service robots is recommended. Moreover, regarding customer revisits, utilitarian value services can delight customers more effectively than hedonic value services.

The stimulus-organism-response model was used to identify the relationships among coolness, perceived value, delight and behavioral intention. Moreover, the authors investigated the impact of coolness on utilitarian and hedonic values. These findings are significant for the development of smart restaurants and provide a critical reference for exploring service robots.

The purpose of this paper is to assess the implications of COVID-19 shocks on household income, food security and the role of social protection in Tunisia.

We used food insecurity classes proposed by FAO and data from the Economic Research Forum (ERF) Middle East and North Africa (MENA) Monitor Household Survey conducted over four waves of COVID-19 (November 2020, February 2021, April 2021 and June 2021). Here, the regression of a multinomial logistic model (MLM) is used to highlight the likelihood that a respondent’s eating habits were degraded by the COVID-19 crisis.

The findings first indicate that low-income and labor income-dependent households are the most vulnerable to shocks induced by COVID-19 and have had their food habits deteriorate considerably. Second, self-produced food by farmers who inhabit rural areas represented a food safety net during the pandemic. Finally, households that received a social transfer did not manage to overcome severe food insecurity.

As a result, the challenges are to extend social protection coverage to households that face transitory poverty.

This is among the first studies to examine the effects of COVID-19 on household income and food insecurity in Tunisia. The study uses a new survey whose main objective is to monitor the impact of health crisis on Tunisian households, taking into consideration the strong labor market fluctuations. Indeed, these fluctuations, when measured against the pre-pandemic period and subsequent periods, would help to determine the impact of the COVID-19 pandemic on households’ well-being.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0867.

The rapid proliferation of Internet of Things (IoT) devices across various domains has created a demand for real-time computing resources that traditional cloud computing models struggle to meet. Fog computing, which brings computation resources closer to IoT devices, has emerged as a promising solution. An automatic service placement framework is needed to use fog computing resources efficiently.

In this study, first a three-layer independent service framework is introduced to define relationships between IoT devices and fog layers, facilitating automatic application deployment. Next, an enhanced version of the equilibrium optimizer (EO) algorithm, inspired by physics, is designed for service placement in fog computing environments.

Simulations reveal that the proposed approach surpasses existing methods, achieving a 99% success rate compared to the closest alternative’s 93%. The algorithm also significantly reduces waiting and planning times for service placement, proving its efficiency and effectiveness in optimizing IoT service deployment in fog computing.

One of the primary limitations is the computational complexity involved in dynamically adjusting to real-time changes in network conditions and IoT workloads. Although improved EO offers improvements in placement efficiency, it may not be fully optimized for highly fluctuating environments. Another important limitation is the uncertainty in node resources. Fog computing environments often face unpredictable changes in the availability and capacity of resources across nodes. This uncertainty can affect the algorithm’s ability to consistently make optimal decisions for IoT service placement.

From a practical perspective, the implementation of the proposed framework and the improved EO algorithm can drastically enhance the efficiency of IoT service deployment in fog computing systems. Organizations that rely on IoT networks, particularly those with critical real-time requirements, can benefit from reduced service placement times and lower failure rates. This can lead to better resource utilization, reduced operational costs and improved overall performance of IoT systems. The commercial impact is evident in industries such as smart cities, healthcare, where fast data processing is crucial.

Our proposed framework has important implications for real-world IoT applications, particularly in areas requiring low latency processing, such as healthcare, smart cities. By reducing service delays and optimizing resource allocation, the framework can significantly improve the quality and reliability of services. Additionally, improved resource management leads to cost savings and better system efficiency, making the technology accessible to a wider range of applications.

Existing resource placement strategies have shown inadequate performance, highlighting the need for more advanced algorithms. This study introduces a three-layer automatic framework for enhancing the application deployment of a fog system beside a novel improved EO algorithm to offer a robust solution for assigning IoT applications to fog nodes.

This research seeks to highlight school partnerships as an approach to improving schools and halting the deterioration of their performance in an environment that has suffered from the consequences of conflict for more than a decade.

The research used the qualitative method, and the data were collected through semi-structured interviews with 20 school leaders and teachers.

The results showed the presence of positive attitudes toward inter-school partnerships and their perception of many benefits, the most prominent of which was increasing social cohesion in school and surrounding communities that suffer from divisions resulting from conflict. A set of obstacles includes legislative obstacles, a low degree of autonomy, low competency of school leaders, a lack of trust and incentives.

This study proposes a range of solutions to address the challenges associated with building partnerships. The research emphasizes the significance the school-to-school partnerships and their positive role in improving the performance of schools in developing countries, especially in environments suffering from the consequences of civil wars and social divisions.

As host to over one million Syrian refugees, Lebanon continues to experience challenges addressing the needs of refugee families. This research examined the experiences of Syrian families with the refugee support system in Lebanon. The purpose of this study was to better understand the strengths and gaps in existing mechanisms of support for these Syrian families, including informal support from family, neighbors and community and more formalized support provided through entities such as nongovernmental organizations and United Nations agencies.

Data were collected from 46 families displaced by the war and living in Lebanon (N = 351 individuals within 46 families). Collaborative family interviews were conducted with parents, children and often extended family.

The data identified both strengths and gaps in the refugee support system in Lebanon. Gaps in the refugee support system included inadequate housing, a lack of financial and economic support, challenges with a lack of psychosocial support for pregnant women and support for disabled youth. Despite these challenges, families and community workers reported informal community support as a strong mediator of the challenges in Lebanon. Furthermore, the data find that organizations working with Syrian families are utilizing informal community support through capacity building, to create more effective and sustainable support services.

This study provides an overview of strengths and gaps in supports identified by refugees themselves. The research will inform the development and improvement of better support systems in Lebanon and in other refugee–hosting contexts.

The study investigates the impact of inflation on the variability of relative prices in the context of Lebanon.

Unlike the traditional method, which relies on the variance of cross-sectional price changes measured at specific points in time to gauge the variability in relative prices, we employ a more appropriate approach. Under this approach, we capture the dispersion in relative prices by estimating how widely (or closely) a set of commodity prices drift apart over a span of time, offering a more comprehensive assessment. Firstly, we employ Johansen’s cointegration test on rolling subsamples to determine the number of statistically significant cointegrating vectors among the prices of 12 major commodity groups. Under this approach, an increase in the number of significant cointegrating vectors indicates a reduction in relative price variability, while a decrease suggests the opposite. Subsequently, we employ ordinary least squares regression to analyze how the fluctuations in inflation affect the variability in relative prices. The sample period ranges from December 2007 to April 2021.

The empirical results indicate that there exists a certain threshold inflation rate corresponding to which the variability in relative prices is minimized. More importantly, consistent with the theoretical predictions, the results suggest that it is not inflation per se, but the deviation of inflation from the 3% threshold level in either direction that causes higher dispersion in relative prices.

The empirical findings from this study have crucial implications for the operation of monetary and fiscal policy. In particular, these findings suggest that stabilizing long-term inflation around a certain threshold rate will not only help to anchor inflation expectations effectively but will also minimize the welfare costs associated with inflation.

Given the rising inflationary pressure in the recent past and its welfare costs, the study assumes crucial importance in understating how fluctuations in inflation distort the relative price structure and eventually cause resource misallocations and economic inefficiency.